A Thesis Submitted for the Partial Fulfilment of the ......I wish to thank Dr. Vipul Patel, Dr. Hiren J. Patel, Dr. Amit Patel, and Prof. Jayesh Patel, Faculty members, V.M. Patel

“TO STUDY THE LEVEL OF FINANCIAL

LITERACY AND ITS IMPACT ON INVESTMENT

DECISION – AN IN-DEPTH ANALYSIS OF

INVESTORS IN GUJARAT STATE”

A Thesis

Submitted for the Partial Fulfilment of the Requirements

For the Degree of

Doctor of Philosophy

IN

MANAGEMENT

Submitted to

GANPAT UNIVERSITY

RESEARCH GUIDE:

Dr. Mahendra S. Sharma

Ph.D., M.B.A. (Marketing)

Pro-Vice Chancellor

Ganpat University

RESEARCH SCHOLAR:

Ms. Harsha Vijaykumar Jariwala

M.B.A. (Finance), B.B.A. (Finance)

Reg. No: MM/001/011/2009

V. M. Patel Institute of Management

Ganpat University, Ganpat Vidyanagar

Mehsana-Gozaria Highway, Mehsana-384012

Gujarat, India.

SEPTEMBER - 2013

ii

PREFACE

Since last decade, the Indian economy has witnessed a number of structural and

fundamental changes in the financial markets. While Indian economy is on growth

trajectory, there is a wide spread realization amongst all in the financial spectrum that for

such growth to be sustainable, a corresponding deepening of financial sector must

precede. And, such deepening is possible, only when individuals and households are

financially literate.

The economies around the world have increasingly considered financial literacy as a key

pillar for the development of a sound financial system. In current times, financial literacy

has gained the attention of policymakers, regulators, governments and several other

organizations. In this area, substantial efforts have been made and resources have been

developed by the financial education providers to promote financial literacy through a

multitude of financial education programmes.

In India, policymakers have recognized financial literacy as an essential life skill.

Developing and promoting financial literacy through financial education has become an

important policy priority that complements financial consumer protection, inclusion and

prudential regulation. In India, the government has set up the Investors Education and

Protection Fund (IEPF) with the objective to support activities relating to investor

education, awareness and protection. The role of IEPF is to educate, empower and protect

investors by equipping them with information, fundamental knowledge and skills to

evaluate their saving/investment/credit options and enabling them to understand the

implications of alternative financial decisions and make the citizens more empowered on

the subject of personal finance by promoting financial literacy, that is crucial in today‟s

financial markets.

“People spend hours in comparing and studying mobile phone

models, before they buy. This is however never replicated when

they buy financial products that have far reaching consequences”.

iii

Due to developments in the financial markets and demographic, economic and policy

changes, financial markets are becoming more sophisticated. Today‟s investors across the

nation, have more options to spend, save and invest their money for a shorter and/or

longer period of time, as compared to their previous generations. These investors have

greater access to a number of credit, saving and investment instruments provided by the

large range of entities through on-line as well as off-line. Under the new pension plan, i.e.

Defined Contribution Plan (DCP) has shifted the financial burden from employer to

employee/ workers in terms of their financially secured retirement.

Overall, due to changing scenario of financial markets, financial products and services

innovations through financial engineering, developments in information and

communication technology, multifaceted features involved in the myriad of financial

products, the speed with which financial markets and new financial instruments have

emerged and/or number of institutions enter into the financial market with the more

complex products, changes in the pension arrangement, increase in the life expectancy and

the role of technology advances in marketing and delivering the financial products and/or

services in the financial services industry, do not only provide more choices to consumers,

but also challenges to understand the benefits and costs associated with the innovations,

and more specifically, the risk-return matrix inherent to each innovation and hence, leave

many individuals ill-equipped to cope up with the sophisticated choices that they need to

make, for wise saving and investment decisions.

This degree of preference towards informed investments decisions requires the investors

to be equip themselves with the fundamental knowledge and skills to evaluate the complex

saving and investment options among the myriad of products and identify those that best

suit their needs and circumstance, as a market with financially illiterate or ill-informed

consumers benefits no one.

Education may play an important role in equipping the individuals with fundamental

knowledge and skills required to evaluate and choose the best alternatives in terms of

financial products and/or services and providers too and to identify those that best suit

iv

their needs and circumstances. This may be especially true for the population which has

been traditionally underserved by the financial system.

On the part of consumers, the financial literacy is essential as it helps consumers

understand how to avoid becoming involved in transactions those are financially

destructive. Financial literacy may help the consumers/ investors to make a more realistic

assessment of given opportunity for saving or investment, enhance the skill and bargaining

power in financial matter, bring financial efficiency in terms of life time utility and

financial well being, active debt management, evaluating and choosing the right financial

product with confidence, control the spending, encourage the saving and investment

behavior and thus, make them prepared for retirement planning.

For financial systems and economy, financial literacy may result into increase in the

demand for financial products and services, greater competition, innovations and

financially engineered products which may satisfy the specific financial need of investors,

self-funding for retirement especially where government would no longer be there to

provide the social security after retirement and may overcome the “procyclicality” in

lending. At community level too, financial literacy may have considerable benefits, in

particular it may be helpful in enhancing the financial inclusion, avoid voluntary exclusion

in the financial markets and increasing the awareness among the investment community

on financial issues, thereby creating an informed citizenry which can evaluate the

appropriateness of government financial policies in an effective and efficient manner.

The absence of financial literacy or low level of financial literacy may result into lack of

healthy financial ways of thinking, lack of necessary financial knowledge and difficulties

in applying financial knowledge, which may lead to poor financial judgments and hence

poor personal financial management. Financially illiterate individual either voluntarily do

financial exclusion or may prefer to get the financial information from unreliable sources,

the analysis of which may result into misallocation of private wealth, can mire the

household into debt and lead to much lower living standards. At a macro level, it can

cause social decline and increase public expenditure in the form of social security.

v

Absence of this knowledge and skill thus may pose a variety of risk to individual, societal

and economy as a whole

Thus, financial literacy is a hugely significant issue for financial systems of any country,

as it both drives and distorts investment behavior, the composition and direction of

demand for products of competing financial sector interests. Thus financial literacy means

empowering the investors to make correct choices when it comes to taking financial

decisions, be it investing/leveraging/ protecting. It is an important element for promoting

financial inclusion and ultimately financial stability. This may help individuals to

prioritize financial goals, make them aware of opportunities and risks associated with the

financial products and help them to invest with specific time horizons to meet their

financial goals and objectives. Thus, the developments in the domestic financial markets

suggest the importance of investigating the level of financial literacy, and its role in

investors‟ investment decision making.

The present study attempts to make significant contribution in the field of financial

literacy in India, where there is no baseline survey/data available and even the concept has

just caught the fancy of policy makers and others. The in-depth review of literature

suggests that the investment decision can be enhanced by developing financial literacy, by

providing the financial education. The study explores financial literacy level of investors

in the state of Gujarat, and describes its relationship with investment decision. Present

study also highlights the association of demographic and socio-economic profile of

investors with their financial literacy level.

This study may help policy makers, authorities, N.G.O., financial planners and institutions

those who are engaged in promotion of financial literacy through financial education with

the objective of converting the country from country of savers to country of informed

investors.

vi

ACKNOWLEDGEMENT

Every mature person in professional life is keenly aware of his/her sense of indebtedness

to many people, who have motivated and influenced his/her intellectual development

ordinarily. This feeling is formally expressed in gestures of acknowledgement. Therefore,

it seems right to acknowledge my gratitude with the sense of veneration to Almighty God

and various people who helped me during this course of investigation. This valuable

guidance and wise direction has enabled me to complete my investigation in a systematic

and smooth manner, obeying the norms of scholastic research.

In an ecstasy of delight, I express my profound sense of gratitude to my esteemed guide

and academic mentor Dr. Mahendra S. Sharma, Professor & Head, V. M. Patel Institute of

Management, Ganpat University, Kherva, Mehsana, for this schololarly, inspiring

supervision, incessant, painstaking efforts and stimulating guidance patronage. In spite of

his multifarious responsibilities, he helped me to accomplish this research successfully.

His consistently affectionate behavior has been much beyond my imagination.

I owe a debt of gratitude to Prof. P. I. Patel, Director, Mehsana District Education

Foundation and Dr. L. N. Patel, Vice- Chancellor, Ganpat University, Dr. D. V. Patel,

Founder, V. M. Patel Institute of Management, Ganpat Univerisity and the management of

Ganpat University for their moral support and motivation. I am also thankful to V. M.

Patel Institute of Management for all the library, infrastructure facility and other

supporting resources provided to me to complete my investigation.

At this juncture, I am thankful to S. K. School of Business Management,

Hemchandracharya North Gujarat University, Patan and B. J. Vainjya Mahavidyalaya,

Sardar Patel University, Vallabh Vidyanagar, from where I did my post graduation and

graduation. I am also thankful to my school Alembic Vidyalaya.

vii

I owe a debt of gratitude to Mr. Andele Antikson, Policy Maker, OECD, Dr. Jatin Pacholi,

Professor, Middlesex University, U.K., Dr. B. A. Prajapati, Head, S. K. School of

Business Management, Patan, Dr. D. M. Pestonjee, Ex-Professor, IIM- A, Dr. Shailesh

Gandhi, Professor, IIM-A, Dr. V. K. Sappovadia, Dr. Akash Patel , Associate Professor,

PDPU, Dr. S. O. Junare, Head, SJPIM, Gandhinagar, Dr. Narayan Baser, Associate

Professor, SJPIM, Gandhinagar, Dr. K. M. Chudasama, Principal, V.M. Patel College of

Management, Ganpat University for their time to time support to prepare the research

instrument.

I am grateful to Dr. Nitin Tike, Senior Vice President, School for Investor Education and

Financial Literacy, National Institute of Securities Market(An Educational initiative of

SEBI), Shri Sudeep Mishra, Deputy General Manager, Office of Investors Assistance and

Education, Western Region Office, SEBI, Shri Hariharan, Chief General Manager, Office

of Investors Assistance and Education, SEBI to motivate me, to review the research

instrument, to provide me the timely suggestion and to broaden my knowledge in the field

of financial literacy by providing their resources and continuous guidance.

I am also thankful to Shri Ramjibhai Mavani, Ex-Member of Parliament and President,

Rajkot Grahak Suraksha Mandal, Rajkot and Shri Malav Choksi, Deputy General

Manager, The Bombay Stock Exchange Ltd.; for helping me to fill up the research

instrument from the different regions of the state of Gujarat.

I am thankful to Dr. Ashwin G. Modi, Associate Professor, S. K. School of Business

Management, Patan; Dr. Nishith Bhatt, Reader, S. K. School of Business Management,

Patan; Dr. P. K. Priyan, Associate Professor, G. H. Patel Institute of Business

Management, Sardar Patel University, Vallabh Vidyanagar for their moral support.

I wish to thank Dr. Vipul Patel, Dr. Hiren J. Patel, Dr. Amit Patel, and Prof. Jayesh Patel,

Faculty members, V.M. Patel Institute of Management for their continuous support to

carry out the analysis of data. I am also thankful to whole teaching staff and non-teaching

staff of V. M. Patel Institute of Management for their continuous support.

viii

A thank is a small word to use for parents. My mother Smt. Mangalaben Jariwala and my

father Shri Vijaykumar Jariwala are a beacon of inspiration and encouragement

throughout my career and allowing me to carry out this study being away from my home. I

am also grateful to my sisters, Neela and Varsha and a brother, Yogen for their continuous

support in various stages of this study.

I am also thankful to all the respondents who have filled the questionnaires with their

sincere efforts and also for sparing their valuable time to fill up the questionnaires, without

whose contribution it was impossible to come out with findings.

The incredible help offered by my colleagues, friends, and past students, whose names are

not mentioned here, but is incomparable and deserve the appreciation. At last, I am highly

obliged to all the persons who helped me directly or indirectly.

Jariwala Harsha V.

I dedicate this thesis to SUDEEP who is the

light in my life and without whose constant

support & endless encouragement, this work

would not have seen the light of the day.

x

EXECUTIVE SUMMARY

This thesis contains five chapters and a bibliography. The thesis is mainly divided into two

sections. The first section deals with an in-depth literature review on financial literacy,

financial behavior and investment decision. The second section covers an in-depth

research analysis to identify the financial literacy level of investors in the state of Gujarat

and its impact on investment decision.

Chapter 1 describes the background of the research and need for the current study. This

chapter also explains the meaning of literacy, historical developments that have been taken

place in the context of conceptualizing and defining the term “financial literacy”, financial

education as an important tool to promote the financial literacy, need for financial

literacy, consequences of financial illiteracy, scope of the term “financial literacy” and

scope of term "financial literacy” for present study. This chapter also gives the outline of

the whole thesis.

Chapter 2 begins with the relevance of financial systems to economic development

through the savings-investment process. To get an in-depth idea for the topic under study

and to support the academic research base to a research topic, the review of literature

presented in this chapter is divided into two sections. The first section of this chapter

incorporates the theoretical framework for this study by including behavioural finance

models to explain investor behaviour, when rational economic models fail to provide

sufficient explanation, followed by in-depth review of literature on studies related to

saving/investment motives and factors that influence the investment decision of investors.

This section also includes review of studies those had measured the association of

demographic factors of investors with investment decisions. It also incorporates the

importance of risk tolerance ability and need for/ sources of information search in the

investment decision making. The second section of this chapter includes analysis of the

studies conducted in various countries for measuring the financial literacy of their citizens.

It also discusses theoretical framework for financial behavior. In this section, review of

xi

literature is presented on various studies those have attempted to establish the relationship

between financial education, financial literacy and various financial behaviour.

The methodological approach adopted for this research is presented in detail in Chapter 3.

The initial part of this chapter talks about the research gap, followed by the research

objectives under study and scope for present research. The exploratory research design is

used. The research design includes the explanation about population for which the

research is conducted followed by the sampling techniques, sampling unit, sample and

sample size, construction of data collection instrument, data collection method, source of

data collection, description of variables used for this study. The second part of this chapter

contains the methodology used by various researchers to measure the financial literacy of

individuals in their studies, pitfalls of the various methods of measuring financial literacy,

difficulties faced by researchers to measure financial literacy and the appropriate method

selected by a researcher to measure the financial literacy level of investors in present

study, after providing sufficient justifications on demerits of other methods available to

measure financial literacy. The discussion on data analysis techniques and hypotheses

conclude this chapter.

Chapter 4 reports the data analysis and interpretation of data, following the objectives

under study. Different tools – frequency and percentage analysis, cross tabulation, chi-

square test, paired t-test, factor analysis, binary logistic regression and simple linear

regression is used for data analysis in details to draw a conclusion. The analysis is divided

into three major sections. The first section of this chapter deals with an in-depth analysis

of survey responses collected from each respondent towards performance test that is used

to measure financial literacy of investors. Financial literacy score, achieved by each

respondent is further divided into two categories to classify the respondents (investors)

into two categories, 1) investors with relatively low level of financial literacy and 2)

investors with relatively higher level of financial literacy. The second part includes the

analysis of investment objectives, existing investment pattern of investors and investors‟

preference towards various investment alternatives. This part also deals with the analysis

of informative variables on the basis of their preference, and the influence of selected

xii

informative variables on investment decision. The analysis is done by applying factor

analysis, identifying the mean score of each factor, and later applying paired t-test. The

factors analysis is also conducted to identify the factors that may influence the investment

decisions of investors. The categories of financial literacy levels, found in the first section

of analysis, are further used to check the association between each demographic and socio-

economic variable of investors and their financial literacy level. For this, purpose chi-

square test is used. To assess the combine impact of demographic and socio-economic

variables of investors on their financial literacy level, a binary logistic regression is

performed. The chi-square test is used to check the association between financial literacy

level of investors and their monthly spending to monthly income ratio and similarly, to

check the relationship between financial literacy level of investors and their monthly

saving to monthly income ratio. Finally, the correlation and simple regression is used to

check the impact of financial literacy level of investment decision of investors.

At the end of this thesis, Chapter 5, concludes the whole research work carried out by the

researcher. This chapter begins with the summary of the whole work. The discussion on

overall findings is presented in a systematic way following the objectives under study.

Based on the present work, the recommendations are given to policy makers, investors and

financial education providers who are engaged in the financial systems. A discussion on

opportunities for future research and the limitations of the present research work are also

noted at the end of this work.

xiii

CERTIFICATE BY GUIDE

This is to certify that this thesis titled “TO STUDY THE LEVEL OF FINANCIAL

LITERACY AND ITS IMPACT ON INVESTMENT DECISION – AN IN-DEPTH

ANALYSIS OF INVESTORS IN GUJARAT STATE” submitted by Harsha Vijakumar

Jariwala, at Faculty of Management Studies, Ganpat University, Mehsana is the bonafide

work completed under my supervision and guidance for the fulfillment of the requirement

for the award of the degree of Doctor of Philosophy (Ph.D.) in management.

Research Guide:



Professor & Head,

V. M. Patel Institute of Management,

Ganpat University,

Ganpat Vidyanagar, Gujarat, India

Forwarded through:



Dean - Faculty of Management Studies,

Ganpat University,


Date:

Place: Ganpat University, Ganpat Vidyanagar.

xiv

DECLARATION BY CANDIDATE

This thesis titled, “TO STUDY THE LEVEL OF FINANCIAL LITERACY AND ITS

IMPACT ON INVESTMENT DECISION – AN IN-DEPTH ANALYSIS OF

INVESTORS IN GUJARAT STATE” is submitted in fulfillment of the requirements for

the award of the degree of Doctor of Philosophy (Ph.D.) in Management to Ganpat

University, Mehsana. I hereby declare that this thesis is based on my original work except

for quotations and citations which have been duly acknowledged. I also declare that this

thesis has not been previously or concurrently submitted to either in whole or in part, for

any other qualification to Ganpat University or other institutions.

Research Scholar:

Jariwala Harsha V.

UGC – NET (Management), M.B.A. (Finance)

Reg. No: MM/001/011/2009

Date:


xv

CERTIFICATE

This is to certify that the thesis titled “To Study the Level of Financial Literacy and its

Impact on Investment Decision –An In-Depth Analysis of Investors in Gujarat State”

submitted by Ms. Harsha V. Jariwala fulfils the suggestions given by doctoral committee

during pre-doctoral seminar held on July 18, 2013, vide Ganpat University letter no. F.

No. 89/GNU/Ph.D./963/2013 dated 29/08/2013 are duly incorporated in this thesis.

Research Guide:



Professor & Head,

V. M. Patel Institute of Management,

Ganpat University,


Forwarded through:



Dean - Faculty of Management Studies,

Ganpat University,


Date:


xvi

THESIS APPROVAL SHEET

The Ph.D. thesis titled “To Study the Level of Financial Literacy and its Impact on

Investment Decision –An In-Depth Analysis of Investors in Gujarat State” submitted

by Ms. Harsha Jariwala has been approved for the award of the degree of Doctor of

Philosophy under the Faculty of Management, Ganpat University, Gujarat, India.

External Examiner:

Research Guide:


Date:


xvii

CONTENTS

Chapter

No.

Particulars Page

No.

Preface ii

Acknowledgement vi

Executive Summary x

Certificate by Guide xiii

Declaration by Candidate xiv

Certificate xv

Thesis Approval Sheet xvi

List of Tables xxi

List of Figures and Charts xxvii

List of abbreviations Xxviii

1 Introduction to research topic – Financial Literacy 1-34

1.1 Background of the research 2

1.2 Need for Study 4

1.3 Introduction to term „Literacy‟ 6

1.4 History of the term “Financial Literacy” 10

1.5 Need for Financial Literacy 20

1.6 Importance of Financial Literacy 22

1.7 Consequences of Financial Literacy 25

1.8 Scope of Financial Literacy 30

1.9 The scope of term “Financial Literacy” for present study 31

1.10 Outline of the Thesis 32

2 Review of Literature 35-109

Part I Investor’s saving and investment decision 36-59

xviii

2.1 Introduction 36

2.2 Indian Financial Systems 36

2.3 Theoretical Framework for Present Study 37

2.4 Investors‟ Saving/Investment Motives 39

2.5 Investment Decision Making and Irrationality 46

2.6 Conclusion 59

Part – II Financial Literacy and Financial Behaviour 60-109

2.7 Introduction 61

2.8 Global Scenario 61

2.9 Domestic Scenario 80

2.10 Theoretical Framework for Financial Behaviour 82

2.11 Studies on Financial Literacy and Financial Behaviour 97

2.12 Conclusion 109

3 Research Methodology 110-151

3.1 Introduction 112

3.2 Research Gap 112

3.3 Objectives of the study 113

3.4 Scope of the study 114

3.5 Research Methodology 116

3.6 Sampling Design 116

3.7 Data collection 119

3.8 Research Instrument 120

3.9 Description of variables 124

3.10 Coding of Variables 136

3.11 Data analysis 139

3.12 Hypotheses of the study 148

3.13 Conclusion 150

xix

4 Data Analysis and Interpretation 152-298


4.2 Frequency distribution showing profile of study‟s

respondents

156

4.3 Analysis of Financial Literacy Questions 161

4.4 Analysis of Existing investment pattern of investors 166

4.5 Cross Tabulation 167

4.6 Preference given to the variables as a Source of Information 174

4.7 Preference towards selected sources of information and their

influence on investment decisions

177

4.8 Reliability and Normality of data 183

4.9 Factor Analysis 188

4.10 Cross Tabulation and Statistical Tests (Explainable variables

and Financial Literacy Level)

228

4.11 Regression Analysis (Binary Logistic Regression) 246

4.12 Association between the financial literacy level of investors

and their monthly expenditure to monthly income ratio.

273

4.13 Association between financial literacy level of investors and

their monthly saving to monthly income ratio.

275

4.14 Regression Analysis: Impact of Financial Literacy Level on

Investment Decision

278

4.15 Conclusion 298

5 Findings and Conclusion 299-323


5.2 Summary of the study 300

5.3 Findings of the study 302

5.4 Conclusion 316

5.5 Recommendations 318

5.6 Limitations of the study 321

xx

5.7 Scope for further research 322

6 Bibliography 324-346

Appendix 347-363

I Data collection instrument - English 347

II Data collection instrument - Gujarati 354

III List of Publications 363

xxi

LIST OF TABLES

CHAPTER 1

Table 1.1 Literacy- Definition, characteristics, pre-requisites and outcomes 09

CHAPTER 2

Table 2.1 Stage of life cycle, corresponding objective- needs and requisite

financial behavior

87

CHAPTER 3

Table 3.1 Description of demographic and socio-economic variables used

under study

125

Table 3.2 Description of variables used as saving/investment alternatives 128

Table 3.3 Description of variables used as preferred source of information

used under study

129

Table 3.4 Description of variables influencing investment decision used

under study

131

Table 3.5 Codes assigned to variables used as preferred source of information

used under study

137

Table 3.6 Codes assigned to variables influencing investment decision used

under study

138

Table 3.7 Methodology adopted by various researchers for measuring

financial literacy

144

CHAPTER 4

Table 4.1 Respondents‟ profile 159

Table 4.2 Overall financial literacy of respondents 162

Table 4.3 Summary of answers given by the respondents under Basic

Financial Literacy Test

163

xxii

Table 4.4 Summary of answers given by the respondents under advanced

financial literacy test

165

Table 4.5 Existing investment pattern of investors 167

Table 4.6 Cross Tabulation of ranks given to Investment Objectives 168

Table 4.7 Mean score of Investment objectives 170

Table 4.8 Cross Tabulation of Rank given for preferred Investment

Alternative

171

Table 4.9 Mean score of each investment alternatives on the basis of ranks

given by the respondents according to their preference

173

Table 4.10 Preference given by respondents towards factors as preferred

source of information

175

Table 4.11 Preference towards selected sources of information and their

influence on Investment Decisions

177

Table 4.12

Paired Sample Statistics 180

Table 4.13 Paired Samples t test values 182

Table 4.14 Cronbach‟s Alpha for the variables of preferred source of

information

184

Table 4.15 Cronbach‟s Alpha for variables influencing investment decision 184

Table 4.16 Data quality for variables of preferred sources of information 185

Table 4.17 Data quality for variables influencing investment decision 186

Table 4.18 KMO and Bartlett's Test 190

Table 4.19 Anti- Image Correlation Matrix 191

Table 4.20 Communalities 192

Table 4.21 Revised Anti- Image Correlation Matrix 193

Table 4.22 Revised Communalities 193

Table 4.23 Total Variance Explained 196

Table 4.24 Component Matrix 197

Table 4.25 Guidelines for identifying significant factor loadings based on

sample size

198

Table 4.26 Rotated Component Matrix 201

xxiii

Table 4.27 Composition of each factor identified in factor analysis 202

Table 4.28 Mean preference score of extracted factors 206

Table 4.29 KMO and Bartlett's Test 207

Table 4.30 Communalities 208


Table 4.32 Anti Image Correlation Matrix (for 29 variables) 212


Table 4.34 Total Variance Explained 215

Table 4.35 Component Matrix 216

Table 4.36 Rotated Component Matrix

218

Table 4.37 Composition of each factor identified in factor analysis 219

Table 4.38 Mean score of extracted factors 226

Table 4.39 Mean score of each variable within each factor 227

Table 4.40 Cross Tabulation of investors‟ age and their financial literacy level 229

Table 4.41 Chi-Square Tests 230

Table 4.42 Symmetric Measures 230

Table 4.43 Cross Tabulation of investors‟ gender and their financial literacy

level

231

Table 4.44 Chi-Square tests 231

Table 4.45 Cross Tabulation of investors‟ education and their financial literacy

level

232


Table 4.47 Cross Tabulation of investors‟ monthly income and their financial

literacy level

234


Table 4.49 Cross Tabulation of investors‟ stage in family life cycle their

financial literacy level

235


Table 4.51 Cross Tabulation of investors‟ employment structure and financial

literacy level

236

xxiv

Table 4.52 Revised Cross Tabulation of investors‟ employment structure and

their financial literacy level

237


Table 4.54 Cross Tabulation of investors‟ type of workplace activity and their


239


Table 4.56 Cross Tabulation of investors‟ years of work experience and their


240


Table 4.58 Cross Tabulation of investors‟ years of investment experience and


242


Table 4.60 Cross Tabulation of numbers of times investors shop around and


243


Table 4.62 Cross tabulation of risk tolerance level of investors and their


245


Table 4.64 Study Variables: Dependent and Independent Variables for Logistic

Regression

251

Table 4.65 Case Processing Summary 252

Table 4.66 Classification Table 253

Table 4.67 Variables not in the Equation 254

Table 4.68 Variables in the Equation 255

Table 4.69 Omnibus Tests of Model Coefficients 257

Table 4.70 Contingency Table for Hosmer and Lemeshow Test 258

Table 4.71 Model fitting information: Test of Significance: Hosmer-

Lemeshow Test

259

Table 4.72 Strength of the relationship model 261

Table 4.73 Significance of each individual predictor on dependent variable 262

xxv

Table 4.74 Classification Table 270

Table 4.75 Cross Tabulation of investors‟ financial literacy level and their

monthly expenditure to monthly income ratio

273

Table 4.76 Revised cross tabulation of investors‟ financial literacy level and

their monthly expenditure to monthly income ratio

274


Table 4.78 Cross Tabulation of investors‟ financial literacy and their monthly

saving to monthly income ratio

275

Table 4.79 Revised cross tabulation of investors with various level of financial

literacy and their monthly saving to monthly income ratio

276


Table 4.81 Correlations between FLL and Personal financial Need 281

Table 4.82 Model Summary 281

Table 4.83 ANOVA 281

Table 4.84 Coefficients 282

Table 4.85 Correlations between FLL and Accounting, Business and Financial

Information

283

Table 4.86 Correlations between FLL and Economic and Regulatory

Environment

284

Table 4.87 Correlations between FLL and Operational Feedback 285

Table 4.88 Correlations between FLL and Advocate recommendation 285




Table 4.92 Correlations between FLL and Overall Group Performance 288




Table 4.96 Correlations between FLL and Credit Features 290

Table 4.97 Correlation between FLL and Personal Inclination 291

xxvi

Table 4.98 Correlations between FLL and Monetary Expectation 291




Table 4.102 Correlations between FLL and sum of Investment Decision Factors 294




Table 4.106 Summary of Regression Analysis of Financial Literacy Level and

Investment Decision

297

xxvii

LIST OF FIGURES AND CHARTS

CHAPTER 1

Fig. 1.1 Conceptual model of financial literacy 17

CHAPTER 2

Fig. 2.1 An individual‟s financial life cycle and corresponding objectives 86

Fig. 2.2 Financial Need Hierarchy 89

CHAPTER 4

Fig. 4.1 Pie chart of classification of respondents 166

Fig. 4.2 Bar chart of ranks given by the Respondents to Investment

Objectives (in per cent)

169

Fig. 4.3 Bar chart of mean score of Investment objectives 170

Fig. 4.4 Bar chart of ranks given by the respondents to investment

alternatives

172

Fig. 4.5 Bar chart of mean score of each investment alternatives on the basis

of ranks given by the respondents according to their preference

174

Fig. 4.6 Bar chart of preference given by respondents towards factors as

preferred source of information

176

Fig. 4.7 Classification Plot 272

xxviii

LIST OF ABBREVIATIONS

AdFLAG : Adult Financial Literacy Advisory Group

ANOVA : Analysis of Variance

ANZ Bank : Australia and New Zealand Banking Group Ltd. (known as ANZ

Bank)

CBF : Commonwealth Bank Foundation

CRY : Child Rights and You

FESC : Financial Education Steering Committee

FINRA : Financial Industry Regulatory Authority

FLEC : Financial Literacy and Education Commission

FLC : Financial Literacy Centres

FLCCC : Financial Literacy and Credit Counseling Centre

FLL : Financial Literacy Level

HNIs : High Net Worth Investors

HRS : Health and Retirement Survey

IEPF : Investor Education Protection Fund

KVP : Kisan Vikas Patra

MNYL : Max New York Life Insurance Company Ltd.

NABARD : National Bank for Agriculture and Rural Development

NAV : Net Asset Value

NCAER : National Council of Applied Economic Research

NCEE : National Council on Economic Education

NEFE : National Endowment for Financial Education

NGO : Non Governmental Organization

NSC : National Savings Certificate

OECD : Organization for Economic Co-operation and Development

PACFL : President Advisory Council on Financial Literacy

PPF : Public Provident Fund

RMR : Roy Morgan Research

xxix

SCF : Survey of Consumer Finance

POMIS : Post Office Monthly Income Scheme

RBI : Reserve Bank of India

SEBI : Securities and Exchange Board of India

SEWA : Self Employed Women‟s Association

SPSS : Statistical Package for Social Sciences

TIAA-CERF : Teachers Insurance and Annuity Association – College Retirement

Equities Fund

UNESCO : United Nations Educational, Scientific and Cultural Organization

Introduction

to Research Topic:

Financial Literacy

Chapter 1

1

1.1 Background of the research

1.2 Need for study

1.3 Introduction to term „Literacy‟

1.4 History of the term “Financial Literacy”

1.5 Need for financial literacy

1.6 Importance of financial literacy

1.7 Consequences of financial illiteracy

1.8 Scope of the term “Financial Literacy”

1.9 The scope of term “Financial Literacy” for present study

1.10 Outline of the thesis

2

1.1 Background of the research

The growth and development of the Indian economy and the expansion of financial

markets through liberalization, privatization and globalization have given a way to a

plethora of financial products either as an investment alternative or a credit one. But, on

the other hand, financial illiteracy or low level of financial literacy prevents the

individuals from making a judicious choice with regard to his/her financial decisions. As

a result, the individuals are not able to choose the most suitable investment alternative

which can beat the rate of inflation prevailing in the economy and give them a net

positive return.

Over the last decade, the Indian economy has grown at a rapid pace. However, this

growth has faced increased pressure from both moderation in investment demand and an

uncertain global environment. Singh (20081) commented that ―….we must not forget that

growth is not the only measure of the development. Our ultimate objective is to achieve

broad based improvement in the living standards for all our people‖ (p.iii).

If growth is sufficiently inclusive, it would certainly provide an environment conducive

to bring about a broad-based improvement in living standards. This improvement in

living standards would seek the distribution of higher quality and quantity of goods and

services to the individuals and to the society, thereby contributing to material well-being.

Thus, for the Indian economy, the growth would need to be accompanied with a broad

based economic development. The basic tenet of ―process of development‖ is given in the

tenth five year plan, which stated that ―The process of development in any society should

ideally be viewed and assessed in terms of what it does for the average individual. The

decade of the 1990s saw a visible shift in the focus of development planning from the

mere expansion of the production of goods and services and the consequent growth in per

capita income to planning for enhancement of human well-being. Later, it was realized

that human development means much more than the rise or fall of national income. It is

1 Singh, M. (2008). ‗Forward‘, Eleventh Five Year Plan 2007-2012, Inclusive Growth, 1, planning

commission, government of India, New Delhi, India: Oxford University Press, p.iii.

3

about the quality of life, the level of human well-being and the access to basic social

service.‖ (Planning Commission, 20032, p.15)

The Planning Commission (20033) has stated that the three critical dimensions of human

well-being as mentioned in the tenth five years plan are (p. 15):

1. Longevity: The ability to lead a long and healthy life.

2. Education: The ability to read, write and acquire knowledge.

3. Command over the resources: The ability to enjoy a decent standard of living and

have a socially meaningful life.

As stated above, the third dimension of human well-being pertains to command over the

resources, which is in the crux of this research study. Money is one of the most

significant resources that form the backbone of any economic system. Oleson (20044)

stated that ―it is the most widely accepted medium of exchange and has a paramount

place in the ability of an individual to fulfill his/her social and material needs like

planning for children‘s education, marriage, own retirement, old age security, etc‖. Hira

et al. (19895) stated that ―the ability to manage effectively the monetary resources would

help individuals to achieve financial satisfaction and financial well-being which would

contribute to their life-satisfaction‖.

Ahuwalia (20086) said ―Indians are wise savers but the poor investors‖. The survey has

revealed that people in India do not plan for long-term future and keep themselves away

from investing in the long-term instruments though they save for long-term goals such as

emergencies, education and old age. The study also noted that Indians prefer to save

2 Planning Commission (2003). Tenth Five Year Plan 2002–2007, Sectoral Policies and Programmes, Vol.

2, New Delhi, India. 3 Ibid, 15. 4 Oleson, M. (2004). Exploring the relationship between money attitudes and Maslow‘s hierarchy of needs. International Journal of Consumer Studies, 28,.83–92, January. 5 Hira, T.H., Fanslow, A.M. & Titus, P.M. (1989). Changes in financial status influencing level of

satisfaction in households‘ Lifestyles. Family and Economic Issues, 10, 107–121. 6 Ahuvalia, M. S. (2006). Speech at launching of the book ―How India Earns, Spends and Saves‖, launched

by Deputy Chairman, Planning Commission, Government of India, Montek Singh Ahluwalia, February 6,

2006. New Delhi.

4

money in ―in-house savings‖ rather than ―in banks or investments‖. They save money for

―emergency and any mis-happening‖. The study concluded that this may pose serious

concern for India, where social security systems are virtually non-existent.

Hence, it is to be noted that, to cope up with the inflation and to navigate the financial

markets, an individual must invest his/her saving in a proper way. This plays a significant

role in the ability of the individual to enjoy a decent standard of living throughout his/her

lifespan. Thus, ability to manage money and take effective actions to plan the current and

future use of money i.e. financial literacy is of paramount importance in the achievement

of the developmental goals of our economic planning. Thus, this understanding of

personal financial management would help the individuals to have a command over the

monetary resources. Beal and Delpachitra (20037) and CBF (2004b

8) observed that

financial literacy skills enable individuals to navigate the financial world, make informed

decisions about their money and minimise their chances of being misled on financial

matters.

1.2 Need for study

Financial literacy has become increasingly important over the past decades. There is a

growing belief that the individual would need to become more self-reliant in the future.

Increased competition and more complex products in the financial services industry leave

many people ill- equipped to cope with the sophisticated choices they may need to make.

Compared to the previous generations, there is now a wide variety of ways individuals

generate and dispose their income. The changes in work life over the world are meant

that the income stream of individuals has become more inconsistent. The changing world

of work has made a inconsistent income over a long period. There are periods of high

income followed by low level of income or no income at all. At the same time, people are

living longer and they need to make a greater provision for retirement, health care and

7 Beal, D.J. & Delpachitra, S.B. (2003). Financial literacy among Australian university students, Economic

Papers, 22(1), 65-78. 8 Commonwealth Bank Foundation (CBF) (2004b). Improving Financial Literacy in Australia: Benefits for

the Individual and the Nation, Research Report, Commonwealth Bank Foundation, Sydney.

5

insurances to cover unpredictable eventualities, where government/state is no longer able

to provide the type of safety net that was available in the past. Given all this, individuals

must have necessary skills to make suitable financial decisions to enable them to be more

in control of their own circumstances and have a secure financial future.

Education can play a critical role in equipping consumers with the fundamental

knowledge required to choose among the myriad of products and providers in the

financial services industry. This is especially true for populations that have traditionally

been underserved by our financial system. In particular, financial literacy education may

help to prevent vulnerable sections of society from becoming entangled in financially

devastating credit arrangements.

In India, policymakers have recognized financial literacy as an essential life skill.

Developing and promoting financial literacy through financial education has become an

important policy priority to complement financial consumer protection, inclusion and

prudential regulation. The national financial education efforts vary according to set-up,

audience and subject matter. Several organizations jointly work to deliver financial

education including regulatory authorities like Reserve Bank of India, Ministry of

Corporate Affairs, Ministry of Human Resource Development, Securities and Exchange

Board of India, Insurance Regulatory and Development Authority, NABARD, Financial

Stability and Development Council, policy makers like OECD, educational institutions

like National Institute for Securities Market and Indian School of Microfinance for

Women, self regulatory organizations such as The National Stock Exchange Ltd. and The

Bombay Stock Exchange Limited, non-governmental organizations like Sanchayan,

SEWA, Meljol, CRY, City India and financial institutions such as ICICI Bank, India

Infoline Ltd., Bank of India, etc. The objectives of this initiative undertaken by these

organizations are to empower the people on the subject of personal finance by providing

them basic knowledge of planning their expenses against their incomes, inculcating the

saving habits so that they can live and enjoy dignified life after retirement.

6

The present study attempts to focus on the existing financial literacy level of retail

individual investors in the state of Gujarat. The researcher has examined the association

between demographic and socio-economic profile of investors and their financial literacy

level. The study also attempts to find whether financial literacy level of investors does

have any impact on their investment decision? Does financial literacy level have any

association with investors‘ monthly expenditure to monthly income ratio and monthly

saving to monthly income ratio? Researcher has also identified the most preferred source

of information preferred by investors while investing and whether these sources of

information do have any influence on investment decision of investors.

Given the lack of any clear approach for promoting financial literacy and that there is no

baseline data available in the Indian context as regards financial literacy, the present

study may provide useful insight to those, who are in the field of financial literacy.

1.3 Introduction to term „Literacy‟

Literacy has traditionally been described as the ability to read and write. It is a concept

claimed and defined by a range of different theoretical fields. The first internationally

agreed definition of literacy was provided in 1958 by The United Nations Educational,

Scientific and Cultural Organization (UNESCO). UNESCO (19589) stated ―a literate

person is one who can, with understanding, both read and write short simple statement

on his or her everyday life‖ (p. 12). This definition has evolved in 2003, when UNESCO

(200310

) proposed an operational definition that attempted to encompass the several

different dimensions of literacy. It had defined literacy as an ―ability to identify,

understand, interpret, create, communicate, compute and use printed and written

materials associated with varying contexts. Literacy involves a continuum of learning in

enabling individuals to achieve their goals, to develop their knowledge and potential and

to participate fully in their community and wider society‖ (p. 13).

9 UNESCO Educational Sector. The Plurality of Literacy and its implications for policies and programs:

Position Paper. [monograph on the Internet]. France: United Nations Educational Scientific and Cultural

Organization, 2004. Retrieved January 30, 2010 from:

http://unesdoc.unesco.org/images/0013/001362/136246e.pdf. 10 Ibid., p. 13.

http://en.wikipedia.org/wiki/UNESCO

7

The Workforce Investment Act (1998), National Institute for Literacy defined literacy as

―an individual's ability to read, write, speak in English, compute and solve problems at

the levels of proficiency necessary to function on the job, in the family of the individual

and in society‖11

. This is a broader view of literacy than just an individual's ability to

read, the more traditional concept of literacy.

Literacy is defined in the Collins dictionary as ‗the ability to read and write‘ or ―the

ability to use language effectively‖. The Oxford English Dictionary defines literacy as

―the quality or state of being literate; knowledge of letters; condition in respect to

education, ability to read and write‖. Literacy is a topic of interest to individuals from a

variety of backgrounds and is of interest for a variety of reasons. Literacy is examined,

researched, discussed and written about by individuals including educators,

psychologists, socio-anthropologists, civil servants, government ministers, researchers,

policy makers and those in the media. Literacy is subjected to a phenomenal level of

enquiry, however the perspectives of these interested parties are inevitably varied, each

drawing its own conclusions according to its area of specialization. Goody (198612

)

argued that ―literacy is ideological, which means that literacy always exists in a context,

in tandem with values associated with that context‖.

Burnet (196513

) explained that literacy is not simply about reading and writing (although

there is nothing simplistic about the acquisition of these skills), but it also includes:

Learning

Achieving Status

Achieving human rights

Knowing

Making Choices

Improving occupational status

11 The National Literacy Act of 1991, Public law 102-73, 105 Stat. 333 (JUL. 25. 1991). 12

Goody, Jack. 1986. The logic of writing and the organization of society. New York: Cambridge

University Press. 0521327458. Location: Dallas SIL Library 303.4 G658. 13 Burnet, M. (1965). ABC of Literacy, Paris: United Nations.

8

Improving leisure pursuits

Making comparisons

Creating and confirming conclusion

Margaret Jackson (199314

), in her book stated ―Literacy offers us access to information,

ideas, opinions and by creating the potential for reflecting, provides opportunities for

making and communicating meaning, and for learning‖ (p. 1). It enables individuals to

make meaning and to learn.

Literacy involves individuals being able to read and write. Jackson‘s definition above

also highlights that these skills on their own are not sufficient for an individual to become

literate; individuals must also be able to reflect in order to make and communicate

meaning and also to learn. This approach again highlights the importance of literacy.

The use of terms ‗offers‘, ‗potential‘ and ‗opportunities‘ indicates again that literacy is

important because of the benefits that arise for those who are literate. It is important to

note that these benefits are all possibilities rather than guaranteed consequences.

Gee (199015

) had added ―literacy as a socially constructed activity and suggests that

literacy contributes towards both, creating the reality in which it operates and is

simultaneously influenced by reality; ‗each has a part in the construction of the other‖

(p.5).

Reading and writing are skills necessary for the attainment of literacy but they do not

constitute literacy itself. Carolyne L.J.M. and Richard M.S.W (200016

) defined, literacy is

to be ―…a process whereby individuals use a combination of their skills and available

resources to make sense of or understand those resources in order to achieve objectives‖

(p. 22).

14 Jackson, M. (1993). Literacy. London: David Fulton Publishers. 15

Gee, J. (1990). Socio Linguistics and Literacies, Basingstoke: Falmer Press. 16 Carolyne L.J. M.,Richard M.S.W. (2000). Conceptualizing financial literacy. Business School Research,

7, Loughborough University, 1-40.

9

Table 1.1 Literacy- Definition, Characteristics, Pre-Requisites and Outcomes

Literacy is: Characteristics Is dependent on Leads to:

Meaning

making

Understanding

Highly valued,

High level of interest,

Concern over

standards,

Has various degrees,

Varies from culture to

culture,

Constantly evolving.

Acquiring

necessary skills/

Technology,

Availability of

resources.

Positive outcomes for both

individual and society

Learning, Achieving status ,

Achieving human rights,

Knowing, making Choices,

Improving occupational status

and wealth, Improving leisure

pursuits, making comparisons,

creating and confirming

conclusions

(Source: Conceptualizing Financial Literacy. Business School Research Paper Series: Paper 2000:7,

Loughborough University, By Carolyne L. J. Mason and Richard M.S. Wilson )

The term literacy is synonymous with understanding or meaning making and this

meaning-making is a prerequisite for the achievement of desired outcomes or objectives.

Mason L. J & Richard M.S.W. (200717

) explained while conceptualizing the term literacy

that ―literacy as a meaning making process which enables informed decisions to be made

in order to achieve desired outcomes‖ (p. 32).

The term literacy is one that has been adopted by practitioners from a variety of

backgrounds. A search of the literature identified a host of descriptions that included

literacy in their title. These included Statistical literacy (Haack, 197918

), Political literacy

(Institute of Education, 198319

), Computer literacy (Day, 198720

), Information literacy

17 Carolyne L.J. M.,Richard M.S.W. (2000). Conceptualizing financial literacy. Business School Research Research, 7, Loughborough University, 1-40. 18 Haack, D.G. (1979). Statistical Literacy – A Guide to Interpretation, North Scituate, Massachusetts:

Duxberry Press. 19 Institute of Education (1983). Teaching political literacy: implications for teacher training and

curriculum planning, University of London, Institute of Education, Paper 16. 20 Day, J.M. (1987). Computer literacy and library and information studies: A literature review, British

Library Research Paper 18, London: BL.

10

(Kulthau, 199121

), Visual literacy (Wilde, 199122

), Tele literacy (Bianculli, 199223

),

Scientific and technological literacy (Layton, 199424

), Multimedia literacy (Hofsteter,

199525

), Internet literacy (Martin, 199726

) and Electronic literacy (Craver, 199727

) and

Financial literacy (Noctor, Stoney and Stradling, 199228

).

The current chapter aims to define financial literacy as a concept by means of a literature

review of the existing definitions on financial literacy, conceptualize the term financial

literacy for current research and its need and importance in the present era and scope of

the term ―financial literacy‖ for present study.

1.4 History of the term “Financial Literacy”

Over the last several years, the issue of financial literacy and financial education has risen

on the agendas of educators, community groups, businesses, government agencies,

organizations, and policy makers. A number of researches have also been done in the

past, on the issue of financial education, either from a policy perspective or a pragmatic

perspective

21 Kulthau, C.C. (1991). Introduction in , Jana Varlejs (ed) (1991) Information Literacy: Learning How to

learn, Proceedings of the Twenty-eighth Annual Symposium of the Graduate Alumni and Faculty of the

Ritgers School of Communication, Information and Library Studies, 6 April 1990, Jefferson: McFarland &

Company. Layton. 22

Wilde, J. (1991). Visual Literacy: A conceptual approach to graphic problem solving, New York:

Watson-Guptill. 23 Bianculli, D. (1992). Teleliteracy, Continuum, New York. 24 Layton, D (1994). Scientific and technological literacy: meanings and rationales: An annotated

bibliography, Leeds: Centre for Studies in Science and Mathematics Education, University of Leeds in

association with UNESCO. 25 Hofsteter, F.T. (1995). Multi-media Literacy, New York; London: McGraw-Hill. 26 Martin, L.H.M. (Ed.) (1997). The Challenge of Internet Literacy: The instruction-Web Convergence.

New York; London: Haworth Press. 27 Craver, K.W. (1997). Teaching electronic literacy: a concepts-based approach for library media

specialists,Westport, Conn; London: Greenwood Press. 28 Noctor M., Stoney S., & Stradling S. (1992) Financial literacy; a discussion of concepts and competences

of financial literacy and opportunities for its introduction into young peoples‘ learning: National

Foundation for Educational Research commissioned by NatWest.

11

Jacob, Hudson, and Bush (200029

) in their report to the Woodstock Institute had stated

that ―financial knowledge has become not just a convenience but an essential survival

tool‖ (p.7). Coussens (200430

) has commented ―the financial product innovation and

marketing, technological advances, consolidation and restructuring of the financial

services industry, changes in retirement and pension plans, and shifts in consumer

attitudes are several trends that are significantly influencing financial attitudes and

decisions‖ and hence challenge the financial literacy.

Hogarth J. M. (200631

) has concluded in his study that ―financial education include: (1)

being knowledgeable, educated, and informed on the issues of managing money and

assets, banking, investments, credit, insurance, and taxes; (2) understanding the basic

concepts underlying the management of money and assets (e.g., the time value of money

in investments and the pooling of risks in insurance); and (3) using that knowledge and

understanding to plan, implement, and evaluate financial decisions‖ (p. 3).

Knapp (199132

) has explained ―modern consumer education is a lifelong process essential

to the economic well-being of society‖. To gather the views about the benefits of

consumer education, he surveyed consumer professionals and found that consumer

education offers the following benefits to individuals: (a) encourages critical thinking, (b)

imparts life skills that contribute to success in everyday living, (c) promotes self-

confidence and independence, (d) fosters broadly accepted values, and (e) improves the

quality of life.

29 Jacob, K., Hudson, S., & Bush, M. (2000). Tools for survival: An analysis of financial literacy programs

for lower-income families. Retrieved on June 27, 2006, from http://www.woodstockinst. 30 Coussens, M. (2005, October). Towards financial literacy: Program leaders comment on evaluation and

impact. Profitwise News and Views, 3-11. Retrieved June 30, 2009, from

http://www.chicagofed.org/community_development/files/10_2005_towards_financial_li teracy.pdf 31 Hogarth , J. M. (2006). Financial education and economic development. Paper presented at Improving

Financial Literacy International Conference hosted by the Russian G8 Presidency in Cooperation with the

OECD. November 29-30, 2006. 32 Knapp, J. P. (1991). The benefits of consumer education. A survey report. Yipsilanti, MI: Eastern

Michigan University,Consumer Education Center.

12

OECD (200533

) defines financial education is ―the process by which financial consumers/

investors improve their understanding of financial products and concepts and, through

information, instruction and/or objective advice, develop the skills and confidence to

become more aware of financial risks and opportunities, to make informed choices, to

know where to go for help, and to take other effective actions to improve their financial

well-being‖ (p. 26).

Where,

Information includes providing consumers the facts, data and specific knowledge to

make them aware of financial opportunities, choices and consequences.

Instruction involves ensuring that individual acquires the skills and ability to understand

the financial terms and concepts through the provisions of training and guidance.

Advice involves providing consumers with counsel about generic financial issues and

products so that they can make the best use of financial information and instruction they

have received.

More concisely, Vitt et al. (200534

) defined financial education as ―…helps the people to

develop the skills those are required to make informed choices and to take action that

improves their financial well-being‖ (p. 9). They also added that the process of helping

people in a financial context is known by various names, such as: investor or investment

education, economic education, financial education, savings education, pension

education, personal finance employee education, workplace financial education,

consumer education, consumer finance protection education, money management

education, retirement savings education and retirement education. They also concluded

that the bottom line of financial literacy is ―… to equip individuals and families with the

ability to negotiate the money management issues necessary for them to make self-

enhancing life choices‖ (p. 9). This focus is very similar to that of the consumer

protection.

33 OECD (2005). Improving Financial Literacy: Analysis of Issues and Policies. Organization for

Economic Co-operation and Development, Paris: OECD Publications. 34 Vitt, L. A., Reichbach, G. M., Kent, J. L., & Siegenthaler, J. K. (2005). Goodbye to Complacency:

Financial Literacy Education in the U.S. 2000-2005. Washington, DC: AARP.

13

Nieuwenhuyzen (200935

) had argued ―financial education is not a consumer protection

and although, it overlaps, the two should not be confused. Both concepts share the same

goals but have different approaches. Financial education provides information,

instruction and advice; consumer protection provides information by means of legislation

and regulation to point out minimum requirements, strengthen protection of consumers,

and provide avenues for redress. Financial education, however has the foremost aim of

improving financial literacy‖ (p. 93).

The President‘s Advisory Council on Financial Literacy (PACFL) (200836

) had defined

financial education as ―the process by which people improve their understanding of

financial products, services and concepts and hereby are empowered to make informed

choices, avoid pitfalls, know where to go for help and take other actions to improve their

present and long-term financial well-being‖. It also states, ―Financial education is a

process through which financial knowledge and skills are gained, rather than the

knowledge and skills themselves. Hence, financial education should be considered a

concept, that promotes financial literacy‖ (p. 4).

Through a number of studies, researchers and policy makers tried to offer a conceptual

definition of financial literacy. Here, breadth of conceptual definitions, drawn from a

number of studies and placed in chronological order. The most common basis for these

definitions is knowledge (or understanding), while some definitions merely requiring

familiarity (arguably a limited form of knowledge). Lusardi & Tufano (200837

) had

emphasized a judgment and decision-making are the aspects of financial literacy. They

have also focused on a specific form of financial literacy – debt literacy.

35 Bernard J. van Nieuwenhuyzen (2009). Financial literacy: As core competency of South African Military

Officers: A Measurement Instrument. (Doctoral dissertation, Stellenbosch University, 2009). Retrieved

May 15, 2010, from Stellenbosch University Digital Theses. 36 The Presidents‘ Advisory Council on Financial Literacy (PACFL) (2008). Annual Report to the President

of U.S. United States Department of The Treasury office of Financial Education. 37 Lusardi, A. & Tufano, P. (2008). Debt literacy, financial experiences, and over-indebtedness. Dartmouth

Working Paper.

14

Noctor, Stoney and Stradling (199238

) undertook a study on behalf of National

Westminster Bank in the U.K., where they have introduced, conceptualized and defined

the term ‗financial literacy‘ as ―the ability to make informed judgments and to take

effective decisions regarding the use and management of money‖(p. 4).

Anthes (200439

) stated that ―personal financial literacy is the ability to read, analyse,

manage and communicate about the personal financial conditions that affect material well

being‖. Mason and Wilson (200040

) have defined, financial literacy as a ―… ‗Meaning-

making process‘ in which individuals use a combination of skills and technologies,

resources and contextual knowledge to make sense of information in order to be

sufficiently informed to make decisions with an awareness of financial consequences‖

(p. 32). They interpreted, financial literacy as ―An individual‘s ability to obtain,

understand and evaluate the relevant information necessary to make decisions with an

awareness of the likely financial consequences‖ (p. 3141

).

Hogarth (200242

) explained financial literacy as ―the ability to read, analyze, manage, and

communicate about the personal financial conditions that affect material well-being. It

includes the ability to discern financial choices, discuss money and financial issues

without (or despite) discomfort, plan for the future, and respond competently to life

events that affect everyday financial decisions, including events in the general economy.

Hence, financial literacy includes knowledge and understanding of basic financial

concepts and the ability to use these to plan and implement financial decisions‖. Hilgert,

38 Noctor M., Stoney S., & Stradling S. (1992) Financial literacy: a discussion of concepts and competences

of financial literacy and opportunities for its introduction into young peoples‘ learning: National

Foundation for Educational Research commissioned by NatWest. 39Anthes, W.L. (2004). Frozen in the headlights: The dynamics of women and money, Journal of Financial

Planning, 13 (9), 130-142. 40 Mason, L. J. & Wilson, M.S. (2000). Conceptualizing financial literacy. Business School Research Paper

Series: Paper 2000:7, Loughborough University. 41 Ibid., p. 31 42 Hogarth, J. M., Hilgert, M. A., & Schuchardt, J. (2002). Money managers: The good, the bad, and the

lost. Proceedings of the Association for Financial Counseling and Planning Education, 12-23.

15

Hogarth & Beverley (200343

) argued that financial literacy is nothing but the financial

knowledge.

FINRA (200344

) stated, ―Financial literacy is the understanding that ordinary investors

have of market principles, instruments, organizations and regulations.‖ (p. 2).

Moore (200345

) argued that ―Individuals are considered financially literate if they are

competent and can demonstrate that they have used knowledge they have learned.

Financial literacy cannot be measured directly so proxies must be used. Literacy is

obtained through practical experience and active integration of knowledge. As people

become more literate they become increasingly more financially sophisticated and it is

conjectured that this may also mean that an individual may be more competent‖ (p. 29).

The U.S. Financial Literacy and Education Commission (200646

) defined financial

literacy as ―the ability to make informed judgments and to take effective actions

regarding the current and future use and management of money‖.

Lusardi and Mitchell (2007c47

) termed financial literacy as ―familiarity with the most

basic economic concepts needed to make sensible saving and investment decisions‖ (p.

36). Lusardi and Tufano (200848

) had focused on debt literacy, a component of financial

literacy, defining it as ―the ability to make simple decisions regarding debt contracts, in

43 Hilgert, M.A., Hogarth, J.M. & Beverly, S.G. (2003) Household financial management: The connection

between knowledge and behavior. Federal Reserve Bulletin, 89 (July): 309-322.Washinton, D.C. 44 FINRA (2003). NASD investor literacy research: Executive summary. Accessed March 30, 2010 at

http://www.finrafoundation.org/surveyexecsum.pdf. 45 Moore, D. (2003). Survey of financial literacy in Washington State: Knowledge, behavior, Attitudes, and Experiences. Technical Report # 03-39. Social and Economic Sciences Research

Center, Washington State Department of Financial Institutions, Olympia, WA . Puulman:

Washington State University. 46 Financial Literacy & Education Commission (2006). Financial Education and Taking Ownership of the

Future: The National Strategy for Financial Literacy. Financial Literacy & Education Commission. 47 Lusardi, A. & Mitchell, O.S. (2007c).Financial Literacy and Retirement Planning: New Evidence from

the Rand American Life Panel. Michigan Retirement Research Center Working Paper 2007-157. 48 Lusardi, A. & Tufano, P. (2008). Debt literacy, financial experiences, and overindebtedness. Dartmouth

Working Paper.

http://www.finrafoundation.org/surveyexecsum.pdf

16

particular how one applies basic knowledge about interest compounding, measured in the

context of everyday financial choices‖ (p. 1).

ANZ Bank (200349

) defined, ―Financial literacy is about enabling people to make

informed and confident decisions regarding all aspects of their budgeting, spending and

saving and their use of financial products and services, from everyday banking through to

borrowing, investing and planning for the future‖ (p. 1). These reports also support the

definitions drawn from Schagen and Lines (199650

) who defined financial literacy as ―the

ability to make informed judgments and to take effective decisions regarding the use and

management of money‖ (p. 1).

However, it is important to note that financial literacy can only ensure individuals are

informed to make decisions, it cannot ensure the 'right' decision is actually made. This is

because individuals do not always make decisions based purely on economic rationality.

Towards composite definition of financial literacy

Financial knowledge is often considered central to financial literacy; it should be

distinguished from general knowledge. For example, Parker et al. (2008) found that

finance-specific knowledge outperformed general knowledge when predicting

performance on a hypothetical investment task.

Angela at el., (200951

) argued, ―Financial knowledge, skills, behavior, and their mutual

relationship should be considered while conceptualizing financial literacy‖ (p. 9). They

have added that, in particular, financial knowledge represents a particularly basic form of

financial literacy. Financial knowledge is reflected in perceived financial knowledge and

influences financial skills that depends on knowledge. Actual financial behavior, in turn

49 ANZ Bank (2003). ANZ Survey of Adult Financial Literacy in Australia. Roy Morgan Research. 50 Schagen, S. & Lines, A. (1996). Financial literacy in adult life: a report to the Natwest Group

Charitable Trust, Slough, Berkshire: National Foundation for Educational Research. 51 Angela, A. H., Parker, A. M., &Yoong K. J. (2009). Defining and measuring financial literacy. RAND

Labor and Population working paper series,708. Department of Labor and The National Institute on Aging

via the RAND Roybal Center for Financial Decision Making.

17

depends on actual knowledge, perceived knowledge, and skills. It is also found that these

relationships are likely to be imperfect, as each also depends on other factors internal and

external to the individual. Thus they have defined ―financial literacy is knowledge of

basic economic and financial concepts, as well as the ability to use that knowledge and

other financial skills to manage financial resources effectively for a life time well being‖

(p. 10). Hogarth, Marianne, & Beverly (200352

) explained that there is a correlation

between financial knowledge and behaviour, although the direction of the causality is

unclear. Figure 1 represents the logical relationships among of financial literacy

components.

(Source: Angella A. Hung, Andrewn M. Parker and Joanne K. (2009). Defining and measuring financial

literacy. Working Paper Series: WR 708. Department of Labor and the National Institute on Aging via the

RAND Roybal Center for Financial Decision Making)

Schagen and Lines (199653

) in a report to the National Foundation for Educational

Research, The United Kingdom, defined financial literacy as ―the ability to make

informed judgments and to take effective decisions regarding the use and management of

money‖. This definition has been later used by number of researchers, where they have

modified this definition. Royal Morgan Research (2003a, 2003b, 2003c) agreed on

financial literacy is about people being informed and confident decision makers in all

aspects of their budgeting, spending, and saving, but the measure of financial literacy

52 Hilgert, M.A., Hogarth, J.M. & Beverly, S.G. (2003). Household financial management: The connection

between knowledge and behavior. Federal Reserve Bulletin, 89 (July): 309-322.Washinton, D.C. 53 Schagen, S. (1997). The Evaluation of NatWest Face 2 Face with Finance. NFER.

18

should reflect individual circumstances and were therefore relative. Whereas knowledge

is ―…. only to be tested against an individual‘s needs and circumstances rather against

the entire array of financial products and services, some of which they neither use nor

need‖ (Roy Morgan Research, 2003c54

).

Alternatively, Beal and Delpachitra (200355

) argued, ―the financially literate should not

only possess the ability to understand the key concepts in money management, a working

knowledge of financial institutions, systems and services and a range of analytical skills,

but also possess a facilitating attitude to effective and responsible management of

financial affairs‖ (p. 65). This particular conceptualization of financial literacy, thus

comprises a skill base incorporating both cognitive (knowledge) and psychological

(willingness and confidence) concepts. In a survey article Hogarth (200256

) observed that

―a consistent theme running through most definitions of financial literacy included being:

1. Knowledgeable, educated and informed on issues of money and assets, banking,

investments, credit, insurance and taxes. 2. Understanding of basic concepts underlying

the management of money and assets and 3. Using the knowledge and understanding to

plan and implement the financial decisions‖. In other words, this study has concluded, the

most definitions of financial literacy include knowledge and understanding of basic

financial concepts and the ability to use these to plan and implement financial decisions.

Coussens (200557

) stated that ―financial literacy represents the culmination of financial

access, education, and understanding, as well as an individual‘s interest, attitude, and

practices that directly benefits the financial efficiency and effectiveness of the individual,

and directly and ultimately benefits that of society at large‖.

54 Roy Morgan Research. (2003c). ANZ Survey of Adult Financial Literacy in Australia: Stage 3: In-Depth

Interview Survey Report, Melbourne: ANZ Bank. 55 Beal, D.J. & Delpachtra, S.B. (2003). Financial literacy among Australian university students, Economic

Papers, 22(1), 65-78. 56 Hogarth, J. M. (2002). Financial literacy and family and consumer sciences. Journal of Family and

Consumer Sciences, 94(1), 14-28. 57 Coussens, M. (2005, October).Towards financial literacy: Program leaders comment on evaluation and

impact. Profitwise News and Views, 3-11. Retrieved June 30, 2009, from

http://www.chicagofed.org/community_development/files/10_2005_towards_financial_li teracy.pdf

19

Studies done by Lusardi & Mitchell (2007a58

, 2007b59

) and ANZ Bank (200860

)

explicitly noted numeracy as a component of financial literacy tests. Further, Peters et al.,

(200661

) explained, ―numeracy is considered as a basic number skill and to be a distinct

construct that is related to and supports financial literacy‖.

Britain‘s Financial Services Authority describes financial capability as encompassing the

outcomes of ―managing money‖, ―planning ahead‖ or retirement planning, ―choosing

products‖ or financial service usage, and product familiarity or financial literacy, which

they termed ―staying informed‖. Atkinson et al., (200662

) and Personal Finance Research

Centre (200563

) stated, ―Financial capability tends to refer to both financial knowledge

and financial management behavior‖. Thus, Financial Capability can be summarized as a

set of financial knowledge, skills and behaviors among individuals. Another group of

researchers Atkinson et al., (200664

), Alba and Hutchinson (200065

), argued that

―financial literacy is a component of financial numeracy‖.

Bruce et al. (200966

) applied the theories of consumer psychology of processing, learning

and knowledge to the ability to comprehend, acquire, and use financial information and

concepts. In their research, they developed a conceptual model of financial numeracy that

incorporates and is rooted in the broader theoretical constructs of cognitive capacity and

prior knowledge, where they defined financial numeracy as a construct of proficiency in

58 Lusardi, Annamaria & Olivia S. Mitchell (2007a). Financial literacy and retirement preparedness:

Evidence and implications for financial education. Business Economics, January, 2007, 35-44. 59 Lusardi, Annamaria & Olivia S. Mitchell (2007a). Financial literacy and retirement preparedness:

Evidence and implications for financial education. Business Economics, January, 2007, 35-44. 60 ANZ Bank (2008). ANZ survey of adult financial literacy in Australia. Retrieved on March 11, 2009

from

http://www.anz.com/Documents/AU/Aboutanz/AN_5654_Adult_Fin_Lit_Report_08_Web_Report_full.pdf 61 Peters, E., Västfjäll, D., Slovic, P., Mertz, C.K., Mazzocco, K., & Dickert, S. (2006). Numeracy and

decision making. Psychological Science, 17, 407-413. 62 Atkinson, A., McKay, S., Kempson, E. & Collard, S. (2006). Levels of Financial Capability in the UK:

Results of a baseline survey, Financial Services Authority, London. 63 Personal Finance Research Centre (2005), Measuring Financial Capability: An Exploratory Study,

available at: www.fsa.gov.uk/pubs/consumer-research/crpr37.pdf 64 Atkinson, A., McKay, S., Kempson, E. and Collard, S. (2006), Levels of Financial Capability in the UK: Results of a Baseline Survey, Financial Services Authority, London. 65 Alba, J.W. & Hutchinson, J.W. (2000). Knowledge calibration: what consumers know and what they

think they know. Journal of Consumer Research, 27 (2), 123-156. 66 Bruce, A. H. & McQuity, S. (2009). A model of consumer financial numeracy. International Journal of

Bank Marketing. 27 (4), 270-293.

http://www.anz.com/Documents/AU/Aboutanz/AN_5654_Adult_Fin_Lit_Report_08_We

20

processing, understanding, acquiring and using financial information and concepts,

numeracy based on a consumer‘s capacity (known as financial capacity) and prior

knowledge (i.e. financial literacy). According to them, financial numeracy has two

distinct components: financial capacity and financial literacy. Financial capacity is the

ability to process and comprehend information and statistics related to financial products,

whereas financial literacy involves adequate knowledge about financial concepts and how

financial products work. In other words, financial capacity is learning-based, whereas

financial literacy knowledge is memory-based.

Kintsch (198867

) explained that ―the financial knowledge can be used to filter,

comprehend, organize, and encode new information that passes through the constraints

imposed by one‘s financial capacity‖.

Operational Definition of Financial Literacy

Financial literacy is a set of skills and knowledge that allows an investor (individual) to

understand

- the financial principles that individual needs to know to make informed decisions

and

- the financial products that impact individual‘s financial well-being.

Here, financial literacy is concerned with the understanding of basic financial concepts,

principles, skills and ability to understand key financial products to make good financial

choices.

1.5 Need for financial literacy

Financial literacy is the process of acquiring knowledge about financial products,

understanding the concept of trade off between risk and return, utilizing the knowledge to

make informed choices and appreciating the available professional knowledge.

67 Kintsch, W. (1988). The role of knowledge discourse comprehension: a construction-integration model.

Psychological Review, 95 (2), 163-182.

21

Former Chairman of the Federal Reserve Bank, Alan Greenspan (200268

) had said,

“[financial education] … can help to inculcate individuals with the financial knowledge

necessary to create household budgets, initiate savings plans, and make strategic investment

decisions. Such financial planning can help families meet near term obligations and

maximize their longer term well being and is especially valuable for populations that have

traditionally been underserved by our financial system.”

Thus, financial literacy may be considered as the ultimate pillar of any financial system,

as it complements the important aspects like greater transparency, policies on consumer

protection and regulation of financial institutions.

Much of the interest shown in financial literacy stems from a concern over people‘s lack

of financial literacy. This is particularly true where individuals are viewed as consumers

of financial products. Schagen and Lines (199669

) expressed the concern about the ability

of these consumers to make effective decisions. The evidence available suggests that

financial information is used ineffectively to make decisions about financial products.

Hogarth (200270

) found that ―financial literacy is important because well-informed, well

educated consumers should make better decisions for their families; increase their

economic security and well-being; contribute to vital, thriving communities; and foster

community economic development‖.

Beal and Delpachitra (200371

) stated, ―the need for financial literacy has grown rapidly

over the last decade because financial markets have been deregulated and credit has

become easier to obtain, as financial institutions compete strongly with each other for

68 Remarks by Chairman Alan Greenspan at the 33rd Annual Legislative Conference of the Congressional

Black Caucus, Washington, D.C., September 26, 2003. Available on the Federal Reserve Board website at

http://www.federalreserve.gov/boarddocs/Speeches/ 2003/20030926/default.html 69 Schagen, S., & Lines, A. (1996). Financial literacy in adult life: a report to the Natwest Group

Charitable Trust. Slough, Berkshire: National Foundation for Educational Research. 70

Hogarth, J. M. (2002). Financial literacy and family and consumer sciences. Journal of Family and

Consumer Sciences, 94(1), 14-28. 71 Beal, D.J. & Delpachtra, S.B. (2003). Financial literacy among Australian university students, Economic

Papers, 22(1), 65-78

http://www.federalreserve.gov/boarddocs/Speeches/

22

market share‖ (p. 65). For millions of households in India, to make independent decisions

regarding financial savings for their retirement calls for a change in the standard of

financial education. Moreover, this increased interest in financial education has been

prompted by the increasing complexity of financial products and the increasing

responsibility on the part of individuals for their own financial security (Mariame and

Hogarth, 200372

, p. 309).

1.6 Importance of financial literacy

The importance of financial literacy is realized when it is put in the perspective of the

following developments in the financial space:

Financial products and services innovation: Growing numbers of consumers are able

to access myriad of financial products and services provided by the variety of providers

through the various distribution channels. Deregulation and liberalization of financial

markets, and reduction of costs through financial engineering, developments in

information and telecommunication have brought many newer financial products and

services tailored to meet very specific market needs. These financial products and

services innovations enabled the consumers to gain access to greater variety of financial

products and provide them more choices to park their savings. The understanding of these

innovations is crucial on the part of consumers, as these innovations do not only provide

more choices to consumers, but also challenges to understand the benefits and costs

associated with the innovations, and more specific the risk-return matrix inherent to each

innovation.

Changing scenario of the domestic financial markets: Many developing countries

have undertaken structural changes in their financial markets and made it more

liberalized, deregulated and open for retail consumers and foreign investors for more

inflow of savings and investments to boost the growth rate of economy. In India, the LPG


between knowledge and behavior. Federal Reserve Bulletin, 89 (July): 309-322.Washinton, D.C.

23

policy along with the deregulation of financial markets has played an important role to

develop the domestic financial market. Post 1991, many important sectors of financial

services industry opened up for private players to gain wider access to consumers. As a

result, not only the giant domestic non-financial services companies have made their

entry, but also foreign companies entered into Indian financial services industry with the

introduction of newer financial products. To compete successfully and to gain market

share, these companies have started to provide generalized and customised financial

solutions and made it easier to obtain credit for consumers of this country, who had

limited prior experience with financial markets and hence, due to lack of experience and

knowledge about the working of financial markets and its products, consumers posses

low awareness about the financial products and services, distrust the modern financial

solutions and prefer traditional avenues for investing their money. As a result, they are

unable to derive optimum financial benefit of the opportunities which these companies‘

financial products/services provide.

Multifaceted features of financial products: The increased complexity of financial

products and services has meant that it is annoying for an average person to be asked to

take financial decision. Perhaps the confusion has arisen not only because of the speed at

which financial markets and new financial instruments have emerged or more number of

institutions providing more complex financial products, but also because of the inability

to understand basic financial concepts. The financial services are divided mainly into two

categories: Saving/ investment services which can be viewed as the instruments for

financing future consumption based on current earnings and credit services i.e. loans/

liabilities which are the instruments for financing current consumption based upon the

future earnings. Latter, is dependent on individual‘s financial needs (or objectives) and

abilities (resources) to acquire these financial assets and liabilities. The combination of

financial need priorities and resource availability at different stages of household‘s life

cycle influences the sequence in which financial services are acquired by the household.

But, nowadays consumers are faced with various financial instruments offering a wide

range of benefits and options with respect to fees, interest rates, length of contract,

exposure to risk etc. The quality of some of these financial products, such as pension,

24

insurance policies etc. and their financial implications on investors are difficult to

understand, as they require long term investment horizon and often they are purchased

infrequently and there is often a significant lapse of time between the investment made

and the return earned. The understanding of multifaceted features of financial products

and services is quite difficult for the average individual which result into greater

perceived risk, need to search greater volume of information to make comparison across a

number of factors which in turn makes decision making more complex, and subsequent

delay in making investment decision.

Increase in an individual‟s responsibility: Nuclear family structure requires an

individual to make number of financial decisions related to spending, saving,

investments, credit etc. not only for himself but also for his family. People also need to

assume more responsibility for funding personal or family healthcare needs. Moreover,

increasing education costs make it important for parents to plan and invest adequately for

their children‘s education.

Increase in the life expectancy, changes in pension agreement and transfer of risk:

Increase in the life expectancy means the possibility of more time spent in retirement and

thus, a greater need of financial planning, expanded insurance, and provisions of health

care related expenses to cover unpredictable eventualities. A case in point is the shift

from Defined Benefit Plan to Defined Contribution Plan, known as New Pension Scheme

(NPS). Since the last decade, there has been a widespread transfer of risk from both

governments and employers to individuals. The governments started to reduce the state-

supported pensions, and some are reducing healthcare benefits. Defined contribution

pension plans are quickly replacing defined benefit pension plans, shifting the

responsibility onto workers to save for their own financial security after retirement. Most

surveys show that a majority of workers are unaware of the risks they now have to face,

and do not have sufficient knowledge and skill to manage such risks adequately, even if

they are aware of them (OECD, 2008).

25

The implementation of New Pension Scheme requires the workers to make various

decisions regarding contribution to plan. As governments will no longer enough to

provide social security, increasing responsibility has come on the shoulders of an

individual. Thus, individuals need to consider not only investment risk and return trade

off, but also uncertainty regarding their life expectancy, attitudes towards risk, current

and future earning potential and likely changes in the personal and social circumstances.

Technological changes and market innovations: Technology advances have

transformed every aspect of processing, marketing and delivery of financial products and

services. The expansion of internet as a mean for communicating and delivering financial

services and/or products has also enabled financial services providers to market the

financial products and serve the customers more effectively and efficiently. These

communication and delivery innovations increase the amount of information available to

consumers enable them to select the best from the myriad of products and services

without geographic limitations. To benefit from innovations, however, consumers must

be financially knowledgeable and literate.

1.7 Consequences of financial illiteracy

As discussed above, to cope up with the financial products and services innovations,

changing scenario of the domestic financial markets, multifaceted features of financial

products, increase in an individual‘s responsibility, increase in the life expectancy,

changes in pension agreement and transfer of risk and technological changes and market

innovations, every individual needs to be financially literate. Chidambaram (200773

) said

that ―financial literacy needs to be embedded in our way of life. Everyone who earns an

income is a potential saver; every saver is a potential investor; every investor ought to be

financially literate‖.

73 Chidambaram, P. (2007) Sesquicentennial Lecture on Financial Literacy, Delivered at Rajiv Gandhi

Centre for Contemporary Studies, University of Mumbai, July 20th. Available at:

http://pib.nic.in/release/release.asp?relid=29306.

26

Lusardi and Mitchell (2007c74

) termed financial literacy as ―familiarity with the most

basic economic concepts needed to make sensible saving and investment decisions‖ (p.

36). Financial literacy also develops the understanding of market principles, instruments,

market participants and regulations. Reddy (200675

) pointed out ―the overriding purpose

of financial literacy is to equip individuals with the capacity to have familiarity with and

understanding of financial products, especially risks and rewards in order to make

informed decisions‖. Jariwala and Sharma (201176

) stated, ―Financial illiteracy or low

level of financial literacy is resulted into lack of healthy ways of financial thinking, lack

of necessary financial knowledge and difficulties in applying financial knowledge‖. They

have also added that ―Financially illiterate individuals either voluntarily do financial

exclusion or get the financial information from unreliable sources, the analysis of which

may be resultant into the misallocation of private wealth and can cause social decline and

increased public expenditure in the form of social security. Absence of this knowledge

and skill poses a variety of risk to individual, society and economy as a whole‖.

Lusardi and Tufano (200977

) found that low levels of financial literacy resulted into an

inability to understand basic financial concepts and poor judgment in borrowing

decisions and retirement planning and hence poor financial management. Poor financial

decisions can slush households in debt and lead to much lower living standards. Cole et

al. (200978

) said that there is a strong association between understanding of financial

concepts, better financial decisions, and household well-being. A compelling body of

evidence demonstrates a strong association between financial literacy and household

well-being. Surveys show that household which demonstrate low levels of financial

74 Lusardi, A. & Mitchell, O.S. (2007c). Financial Literacy and Retirement Planning: New Evidence from

the Rand American Life Panel. Michigan Retirement Research Center Working Paper, 2007-157. 75 Reddy, Y. V. (2006). The Role of Financial Education: The Indian Case. Available at:

http://www.rbi.org/review/r060921b.pdf, retrieved on July 20, 2011. 76

Jariwala, H. & Sharma, S. (2011). Financial literacy: A call for an attention. International Journal of

Academic Conference Proceedings, 1(1), Proceedings of Conference on Inclusive and Sustainable Growth. 77

Lusardi, A. & Tufano, P. (2008). Debt literacy, financial experiences, and overindebtedness. Dartmouth

Working Paper. 78 Cole, S., Thomas, S., & Zia, B. (2009). Financial literacy, financial decisions, and the demand for

financial services: Evidence from India and Indonesia.‖ Harvard Business School Working Paper, 09-117.

http://www.rbi.org/review/r060921b.pdf

27

literacy are those who tend not to plan for retirement (Lusardi & Mitchell, 2007a79

),

borrow at high rates (Stango & Zinman, 200680

), and acquire fewer assets (Lusardi &

Mitchell, 2007b81

). Financial illiteracy or low level of financial literacy resulted into

financial stress. Bagwell (200282

) found that poor financial management leads to greater

absenteeism at work. Hendrix et al. (198783

) and Jacobson et al. (199684

) found that

financial stress was one of the stressors that affect absenteeism. Ullah (199085

) found that

financial stress influences psychological well-being and also mediates the effect of

income and mental health. Kinnenun and Pulkkinen, (199886

) found that these financial

problems are often the basis for divorce, mental illness and a variety of other unhappy

experiences. Having financial literacy skills is essential for avoiding and solving financial

problems, which in turn are vital to a prosperous, healthy and happy life (CBF, 2004a, p.

4). Drentea and Lavrakas (200087

) found that individual who reported higher level of

financial stress showed higher level of physical impairment and illness than lower level

of financial stress. Further, CBF (2004a88

) and Morton (200589

) and support, the high

number of people with low levels of financial literacy presents a serious problem for both

the economic well-being of nations and the personal well-being of such individuals and

79 Lusardi, Annamaria & Olivia S. Mitchell (2007a). Baby Boomer Retirement Security: The Role of

Planning, Financial Literacy, and Housing Wealth. Journal of Monetary Economics, 54, 205–224. 80 Stango, V. & Zinman, J. (2006). How a cognitive bias shapes competition: Evidence from consumer

credit markets. 81 Lusardi, Annamaria & Olivia S. Mitchell (2007b). Financial Literacy and Retirement Preparedness:

Evidence and Implications for Financial Education. Business Economics, January 2007, 35-44. 82 Bagwell, D.C. (2000). Work and Personal Financial Outcomes of Credit Counseling Clients. (Doctroal

Dissertation, Virginia Polytechnic Institute and State University, 2000) Blacksburg. 83 Hendrix, W.J., Steel, R.P. & Shultz, S.A. (1987). Job stress and life stress: Their causes and

consequences. Journal of Social Behavior and Personality, 2(3), 291-302. 84 Jacobson, B. H., Aldana, S. G., goetzel, R. Z., Vardell, K. D., Adams, T. B. & Pietras, R. J. (1996). The

relationship between perceived stress and self-reported illness-related absenteeism. American Journal of

HealthPromotion, 11(1), 54-61. 85 Ullah, P. (1990). The association between income, financial strain and psychological well-being among

unemployed youths. Journal of Occupational Psychology, 63, 317-330. 86 Kinnunen, U., & Pulkkinen, L. (1998). Linking economic stress to marital quality among Finnish marital

couples. Journal of Family Issues, 19, 705-724 87 Drentea, P. & Lavrakas, P.J. (2000). Over the limit: The association among health status, race and debt.

Social Science & Medicine, 50, 517-529. 88 Commonwealth Bank Foundation (CBF), 2004a, Australians and Financial Literacy, Commonwealth

Bank Foundation, Sydney. 89 Morton, J. S. (2005). The interdependence of economic and personal finance education. Social

Education, 69, 66-70.

28

their family. Perry and Morris (200590

) stated that ―there are substantial negative costs to

consumers and the society when consumers lack financial knowledge‖ (p. 310).

Surveys also demonstrate that the adults do not possess the basic knowledge needed to

make informed financial choices. Beal and Delpachitra (200391

) stated, ―Since

governments world-wide are moving down the path of encouraging their citizens to take

more responsibility for their retirement incomes and to move away from public pensions‖

(p. 65). Compared to previous generations, today there is a variety of ways individuals

generate and dispose of their income. The changes in the work life over the world have

meant that the income stream of individuals has become more inconsistent over a long

period. There are periods of high income followed by low level of income or no income

at all. At the same time, people are living longer and they need to make greater provision

for retirement, health care and insurances to cover unpredictable eventualities and the

state would not be longer enough to provide financial security which was available in the

past. So, today individuals must have necessary skills to make informed financial

decisions among the myriad of products and services, which may allow them to secure

their future in financial terms. Beal and Delpachitra (200392

) and CBF (2004b93

) said

that the financial literacy skills enable individuals to navigate the financial world, make

informed decisions about their money and minimise their chances of being misled on

financial matters.

Hogarth, Marianne & Beverly (200394

) stated ―there is a correlation between financial

knowledge and behaviour, although the direction of the causality is unclear. Those who

scored higher on the financial literacy tests, were more likely to follow the recommended

financial practice and recommended financial behaviour‖ (p. 311).

90 Perry, V.G. & Morris, M.D. (2005). Who is in control? The role of self-perception, knowledge, and

income in explaining consumer financial behavior. Journal of Consumer Affairs, 39, pp.299–313. 91

Beal, D.J. & Delpachtra, S.B. (2003). Financial literacy among Australian university students, Economic

Papers, 22(1), 65-78. 92 Beal, D.J. & Delpachtra, S.B. (2003). Financial literacy among Australian university students, Economic

Papers, 22(1), 65-78. 93 Commonwealth Bank Foundation (CBF) (2004b) Improving Financial Literacy in Australia: Benefits for

the Individual and the Nation, Research Report, Commonwealth Bank Foundation, Sydney. 94 Hilgert, M.A., Hogarth, J.M. & Beverly, S.G. (2003). Household financial management: The connection

between knowledge and behavior. Federal Reserve Bulletin, 89 (July): 309-322.

29

Financial education is important not only for the investor or his/her family, but also the

community mass as well. Again, there is a difference between providing information and

providing education, where education may require collection of information, skill

building and motivation on the right time to make the desired changes in behaviour.

Hilgert, Hogarth, & Beverly (200395

) also agree that financial knowledge appears to be

directly correlated with self-beneficial financial behaviour. Mandell (200996

) states,

―Financial behaviour seems to be positively affected by financial literacy, however the

long term financial education on financial behavior are less certain‖ (p. 10).

Personal financial literacy prepares an individual to manage money, credit, and debt,

effectively. Better informed consumers make more effective choices and more

appropriate decisions. They are less likely to be mis-sold or mis-buy products and

services. From a broader perspective, market operations and competitive forces are

compromised when consumers do not have the skills to manage their finances effectively.

As financially knowledgeable consumers demand products that meet their short term and

long term financial needs. Hence, it helps to create a more competitive and more efficient

financial market.

The findings of recent survey97

, found that; In India due to the lack of social security

system, over 80% of Indians save, where 36 % of Indian households keep their savings at

home. While 51 % household keep their saving in bank deposits, and stock and insurance

accounted for only 3 % of estimated household income (out of given alternatives). 74 %

Indians are aware about life insurance, but only 24 % households own life insurance

cover. And due to inability to manage the personal finance, in India, 25 % households are

financially vulnerable.


between knowledge and behavior. Federal Reserve Bulletin, 89 (July): 309-322.Washinton, D.C. 96 Mandell, L. (2009, January).The impact of financial education in high school and college on financial

literacy and subsequent financial decision making. Presented at the American Economic Association

Meetings San Francisco, CA. 97 Result drawn from a survey report ―How India Earns, Spends and Saves‖ done by National Council of

Applied Economic Research (NCAER) & Max New York Life Insurance Company Ltd. 2009.

30

Looking to the recent scenario of Indian financial market, the Indians are having a high

propensity to save, but they choose to put their money in low-yielding instruments and

one of the factors responsible for this is lack of financial plan for future. Furthermore,

‗misplaced financial optimism‘ is a direct fallout of the lack of financial literacy among

Indian households.

Thus, people are suffering from the financial disease like underinsurance, debt trap,

insufficient retirement fund, low return on investment etc., and the cause of all these is

one and the same i.e. ‗Financial Illiteracy‘.

1.8 Scope of Financial Literacy

Roy Morgan Research (200398

) explained the scope of the term ―financial literacy‖ is not

limited up to mathematical literacy and standard literacy, but it also includes knowledge

and understanding, behaviour, attitudes, perceptions and awareness towards financial

world. This includes:

1. Mathematical Literacy and Standard Literacy

- Essential mathematical, reading and comprehension skills

2. Financial Understanding

- Understanding of what money is and how it is exchanged

- Understanding of where money comes from and goes

3. Financial Competence

- Understanding the main features of basic financial services

- Understanding financial records and appreciating the importance of

reading and attitudes to spending money and saving

98 Roy Morgan Research . (2003). ANZ Survey of Adult Financial Literacy in Australia. ANZ Banking

Group.Melbourne: Roy Morgan Research.1-77.

31

- Awareness of risks associated with some financial products and

appreciation of the relationship between risk and return

4. Financial Responsibility

- Ability to make appropriate personal life choices about financial issues

- Understanding consumer rights and responsibilities

- Ability and confidence to access assistance when things go wrong

1.9 The scope of term “Financial Literacy” for present study

To explore the level of financial literacy, basic financial literacy and advanced financial

literacy will be used. The scope of term basic financial literacy is mentioned as follows.

A. Basic Financial Literacy (Financial Competence)

Knowledge and understanding of basic financial concepts, principles and numeracy,

that includes:

1. Scope of investment 2. Financial worth

3. Concept of disposable income 4. Types of Bank accounts

5. Numeracy 6. Compounding

7. Concept of inflation 8. Time value of money

9. Functioning of stock market 10. Diversification

11. Risk return trade off 12. Risk

13. Risk return trade off of two assets 14. Relationship between investment time

horizon and asset growth

15. Relationship between investment time

horizon and fluctuation

16. Asset allocation

17. Relationship between interest asset

prices

18. Consumer rights and responsibility

19. Regulatory body as a part of market

structure

20. KYC

32

B. Advanced Financial Literacy (Product Literacy)

Understanding the features of various financial services/investment instruments,

covering:

1. Fixed deposit 2. National Saving Certificates

3. Public Provident Funds 4. Employee Provident Funds

5. Equity Shares 6. Preference Shares

7. Mutual Funds 8. Debentures and bonds

9. Post Office Monthly Income Schemes 10. Insurance Policy

1.10 Outline of the thesis

This thesis contains five chapters and a bibliography. The thesis is mainly divided into

two sections. The first section deals with an in-depth literature review on financial

literacy, investment decision and financial behavior. The second section covers an in-

depth research analysis to identify the financial literacy level of investors in the state of

Gujarat and its impact on investment decision.

Chapter 1 describes the background of the research and need for the current study. This

chapter also explains the meaning of literacy, historical developments that have been

taken place in the context of conceptualizing and defining the term ―financial literacy‖,

financial education as an important tool to promote the financial literacy, need for

financial literacy, consequences of financial illiteracy, scope of the term ―financial

literacy‖ and scope of term "financial literacy‖ for present study.

Chapter 2 begins with the relevance of financial systems to economic development




33




investment motives and factors that influence the investment decision of investors. This

section also includes review of studies those had measured the association of

demographic factors of investors and investment decisions. It also incorporates the

importance of risk tolerance ability and need for/ sources of information search in

decision making. The second section of this chapter includes analysis of the studies

conducted in various countries for measuring the financial literacy of their citizens. It also

discusses theoretical framework for financial behavior. In this section, review of

literature is presented on various studies those have attempted to establish the relationship

between financial education, financial literacy and various financial behaviour.

The methodological approach adopted for this research is presented in detail in Chapter 3.

The initial part of this chapter talks about the research gap, followed by the research

objectives under study and scope for present research. The exploratory research design is

used. The research design includes the explanation about population for which the

research is conducted followed by the sampling techniques, sampling unit, sample and

sample size, construction of data collection instrument, data collection method, source of

data collection, description of variables used for this study. The second part of this

chapter contains the methodology used by various researchers to measure the financial

literacy of individuals in their studies, pitfalls of the various methods of measuring

financial literacy, difficulties faced by researchers to measure financial literacy and the

appropriate method selected by a researcher to measure the financial literacy level of

investors in present study, after providing sufficient justifications on demerits of other

methods available to measure financial literacy. The discussion on data analysis

techniques and hypotheses concludes this chapter.

Chapter 4 reports the data analysis and interpretation of data, following the objectives

under study. Different tools – frequency and percentage analysis, cross tabulation, chi-

square test, paired t-test, factor analysis, binary logistic regression and simple linear

34

regression is used for data analysis in details to draw a conclusion. The analysis is

divided into three major sections. The first section of this chapter deals with an in-depth

analysis of survey responses collected from each respondent towards performance test,

that is used to measure financial literacy of investors. Financial literacy score, achieved

by each respondent is further divided into two categories to classify the respondents

(investors) into two categories, 1) investors with relatively low level of financial literacy

and 2) investors with relatively higher level of financial literacy. The second part includes

the analysis of investment objectives, existing investment pattern of investors and

investors‘ preference towards various investment alternatives. This part also deals with

the analysis of informative variables on the basis of their preference, and the influence of

selected informative variables on investment decision. The analysis is done by applying

factor analysis, identifying the mean score of each factor, and later applying paired t-test.

The factors analysis is also conducted to identify the factors that may influence the

investment decisions of investors. The categories of financial literacy levels, found in the

first section of analysis, are further used to check the association between each

demographic and socio-economic variable of investors and their financial literacy level.

For this, purpose chi-square test is used. To assess the combine impact of demographic

and socio-economic variables of investors on their financial literacy level, a binary

logistic regression is performed. The chi-square test is used to check the association

between financial literacy level of investors and their monthly spending to monthly

income ratio and similarly, to check the relationship between financial literacy level of

investors and their monthly saving to monthly income ratio. Finally, the correlation and

simple regression is used to check the impact of financial literacy level of investment

decision of investors.

At the end of this thesis, Chapter 5, concludes the whole research work carried out by the

researcher and it discusses the overall findings following the objectives under study. A

discussion on opportunities for future research and the limitations of the present research

work are also noted.

Review of literature

Chapter 2

Investors’ Saving

and

Investment Decision

Part I

35

2.1 Introduction

2.2 Indian Financial Systems

2.3 Theoretical Framework for Present Study

2.4 Investors‟ Saving/ Investment Motives

2.5 Investment Decision Making and Irrationality

2.5.1 Risk Tolerance and Investment Decision

2.5.2 Financial Information and Investment Decision

2.6 Conclusion

36

2.1 Introduction

This chapter begins with the relevance of financial systems to economic development







investment motives and factors that influence the investment decision of investors. This

section also includes studies those had measured the association of demographic factors

of investors with investment decisions. It also incorporates the importance of risk

tolerance ability and need for/ sources of information search in decision making. The

second section of this chapter includes analysis of studies conducted in various countries

for measuring financial literacy of their citizens. It also discusses theoretical framework

for financial behavior. In this section, review of literature is presented on various studies

those have attempted to establish the relationship between financial education, financial

literacy and various financial behaviour.

2.2 Indian Financial Systems

Financial systems are of crucial significance of capital formation. It needs no reiteration

that adequate capital formation is indispensable to a speedy economic growth and

development. The main function of capital markets the collection of savings and their

distribution for industrial investment, thereby stimulating the capital formation and, to

that extent, accelerating the process of economic growth. The process this capital

formation involves three distinct, although inter-related activities.

1) Savings: The ability by which claims to resources are set aside and become

available for the other purpose.

37

2) Finance: The activity by which claims to resources are either assembled from

those released by domestic savings, obtained from abroad, or specially created

usually as bank deposits or notes and then placed in the hands of investors.

3) Investments: The activity by which resources are actually committed to

production.

The volume of capital formation depends upon the intensity and efficiency with which

these activities are carried on. The effective mobilization of savings, the efficiency of the

financial organization and the channelization of these savings into the most desirable and

productive forms of investment are all inter-connected and have a great bearing on the

contribution of capital formation to the economic development. Their relevance to the

savings-investment process is derived from what is called transfer process.

The efficient, articulate and developed financial system is indispensible for this speeder

transfer process, and hence for rapid economic growth and development of a country.

The broad based organization structure of Indian financial system comprises of three

interdependent components: 1) Financial Markets, 2) Financial Institutions/intermediaries

and 3) Financial assets/ instruments/ securities/ services available for saving/investment.

2.3 Theoretical Framework for Present Study

Economic theory on investment decision treats the investment decision of the individual

as a macroeconomic aggregate and the microeconomic foundations of it are drawn from

intertemporal utility theory. Under the standard assumption of this theory, decision

makers are perfectly rational and able to fully utilize all the information available.

Accordingly, individuals maximize their utility based on classic wealth criteria making a

choice between consumption and investment through time. It suggests that they make

optimum choices that maximize the expected value of their private utility, based on

preferences that are consistent across time and independent of context profile.

38

However, some empirical research studies appeared in 1970s focused on the individual

rather than aggregate investor. They found that the assumptions of this traditional

economic utility theory is far from approaching the reality of everyday human being, and

economists have long argued that they were never meant to do so- rather, they provide

mathematically tractable and empirical reasonable approximations for modeling and

analysis of actual behaviour.

A growing body of evidence across multiple domains of observed behaviour however

suggests that this rationale does not always hold true- it finds systematic biases and

anomalies as well as common decision making heuristics that contradict the predictions

of models populated soley by homo economicus. The emerging field of behavioural

economics and its related discipline i.e. behavioural finance, provide theoretical

framework for this study increasingly questioning the notion of absolute rationality.

Rationality itself is bound by context and directed to personal and community ends.

There is no one rational outcome for every financial decision. This discipline also draws

on insights from psychology and cognitive scientists to study aspect(s) of individual

behaviour in various market settings and deviated from this standard assumption. While

explaining behavioural economics DellaVigna (200999

) considers three broad categories

of anomalies or deviations from the standard model, namely, non-standard preference,

non-standard beliefs and non-standard decision making processes. Glaser (2004100

) added

behavioural finance theory incorporates findings from psychology and sociology into its

theory, and uses behavioural finance models to explain investor behaviour or market

anomalies when rational models fail to provide sufficient explanation. Researches in

behavioural finance produced three major theoretical streams, namely: Prospect Theory,

Regret Aversion and Self Control.

The psychological phenomenon explains the reasons for which why do investors behave

irrationally are: representativeness heuristic; conservatism; overconfidence and self-

99 DellaVigna, S. (2009). Psychology and Economics: Evidence from the field. Journal of Economic

Literature, 47 (2), 315-372. 100 Glaser, M., Noth, M. & Weber, M. (2004). Behavioural finance. In D. J. Koehler & N. Harvey (Eds.),

Blackwell Handbook of Judgment & Decision Making, Oxford: Blackwell, pp. 527-546.

39

attribution. Representativeness heuristic explains that after a series of positive earnings,

the investor is most likely started to believe that the next period earnings will again be

positive and fail to consider the probability of a decrease. Conservatism defined as the

process by which individuals modify their beliefs in light of new information. Not only

are beliefs based on short run trends, but the principle of conservatism suggests that

individuals are slow to modify their beliefs in light of new information. In experiments,

individuals are found to update their prior beliefs in the right direction but comparatively,

still not enough to the rational benchmark that assumes full weight is given to all new

information. Investors subject to conservatism might ignore the full information newly

came to the market and take the decision. The behaviour finance also suggests that

investors tend to overestimate the precision of their knowledge. Literature suggests that

people overestimate their ability to do well on tasks and these overestimates increase with

the personal importance of the task. People tend to be unrealistically optimistic about

future events. Each of these research disciplines captured and analyzed behavioural

attributes of individual investors related to his/her own finances.

With regard to financial behaviour, Xiao (2008101

) said that ―financial behaviour can be

defined as any human behaviour that is relevant to money management. The common

financial behaviour includes cash, credit, saving and investment‖ (p. 70).

2.4 Investors‟ Saving/ Investment Motives

Saving may be regarded as a process undertaken by consumers and may be calculated by

the balance from disposable income after accounting for current expenditure. Warneryed

(1999102

) said that ―from a psychology point of view, saving is considered as the result of

a deliberate decision making process and to save as the act of regularly keeping away

some resources for a goal.‖

101 Xiao, J. J. (2008) Handbook of Consumer Finance Research. 102 Warneryd, K.E. (1999). The psychology of saving. A study of economic psychology. Cheltenham:

Edward Elgar Publishing.

40

Goodfellow J. H. (2007103

) said that ―saving is a routine decision may occur where a

consumer‘s monthly consumption expenditure is consistently and significantly below the

level of their monthly income, albeit subject to fluctuations‖ (p. 46).

In economics, saving has been the object of intense theoretical and empirical concern.

(i.e. Keynes‘s, Modi-gliani‘s, Friedman‘s and Duesenberry‘s theories); in psychology it

has been treated from a variety of points of view. Since the early studies of Katona

(1975104

), some have focused on the influence of personality traits, such as the ability to

delay gratification, self-control, aversion to risk, locus of control, time-preference (Daniel

& Webley, 1998105

; Livingstone & Lunt, 1993106

; Lunt & Livingstone, 1991107

). Others

have analyzed the effect of socio-economic variables (age, education, income), habits,

and attitudes (Furnham, 1985108

, 1999109

) showing that the decision to save, although

influenced by economic factors, involves complex psychological and socio-psychological

processes.

People‘s decision regarding how much to save and invest for future depends upon the

trade-off between immediate and future consumption. Freidman (1957110

) modeled this

trade-off as a problem of optimizing utility or happiness over life span. Within this

framework, optimal saving and consumption path depends on how much people value the

consumption at different times in the future. For example, people put higher value on

immediate consumption because the effects of declining health result in less enjoyment

103 Goodfellow, J. H. (2007). Consumer perceptions and attitudes towards savings and investments.

International Journal of Bank Marketing , 32-48. 104 Katona, George (1975). Psychological Economics. New York: Elsevier. 105 Daniel, T., & Webley, P. (1998). Individual differences and research into saving. Talk given at a

workshop on Individual Differences in Economic Behaviour held at the International Centre for Economic

Research, Turin, March 1998. 106 Livingstone, S., & Lunt, P. (1993). Savers and borrowers: Strategies of personal financial management.

Human Relations, 46, 943–985. 107 Lunt, P., & Livingstone, S. (1991). Psychological, social and economic determinants of saving:

Comparing recurrent and total savings. Journal of Economic Psychology, 12, 621–641. 108 Furnham, A. (1985). Why do people save? Attitudes to, habits of, saving money in Britain. Journal of

Applied Social Psychology, 15, 354–373. 109 Furnham, A. (1999). The saving and spending habits of young people. Journal of Economic Psychology,

20(6), 677–697. 110

Friedman, M. (1957). A Theory of the Consumption Function. Princeton, NJ: Princeton University Press.

41

from consumption in on old age. Some people strongly prefer present consumption to

future consumption causing them rationally to choose not to save.

There are a variety of motives for household savings. In broad terms, these motives can

be grouped into four categories: to provide resources for retirement, to finance expected

large life time expenditure (including house purchase and education), to finance

unexpected losses of income (precautionary saving), and to smooth the availability of

financial resources over time to maintain a more stable consumption profile.

The theme of saving motives was first identifies by Keynes (1936111

). He found motives

to save are relatively consistent over time and the likelihood to consume is affected by

saving motives. He identified eight different saving motives: (1) ‗‗Precaution‘‘, which

implies building up a reserve against unforeseen contingencies; (2) ‗‗Foresight‘‘, which

includes providing for anticipated future differences between income and expenditure

(the life-cycle motive); (3) ‗‗Calculation‘‘, which refers to the wish to earn interest; (4)

‗‗Improvement‘‘, which means to enjoy a gradually improving standard of living over

time; (5) ‗‗Independence‘‘, which refers to the need to feel independent and to have the

power to do things; (6) ‗‗Enterprise‘‘, which means having the freedom to invest money

if and when it is favourable; (7) ‗‗Pride‘‘, which concerns leaving money to heirs (the

bequest motive); and (8) ‗‗Avarice‘‘ or pure miserliness. Browning and Lusardi (1996112

)

have added a further motivation to this list, the down-payment motive, which is the desire

to accumulate lump sums to use as down payments for expensive and durable goods such

as a house or a car.

Katona (1975113

) identified the following savings motives (in order of importance):

emergencies (ill-health or unemployment), reserve funds for necessities, retirement or old

age, children‘s needs, buying a house or durable goods, and holidays. Few individuals

were motivated to save for future income (in the form of interest or dividends) or to leave

money to heirs.

111 Keynes, J. M. (1936). The General Theory of Employment Interest and Money. London: Macmillan. 112 Browning, M., & Lusardi, A. (1996). Household saving: Micro theories and micro facts. Journal of

Economic Literature, XXXIV(4), 1797–1855 113

Katona, G. (1975). Psychological economics. New York: Elsevier.

42

Lindqvist (1981114

) had proposed hierarchical structures of saving motives and has

included reasons for savings, in which at the lowest level is the need to handle cash to

deal with short-term financial goals and at the second level, the need to have a reserve of

money as a precautionary measure. At the third level is the need to have a large amount

of money to buy something expensive and finally at the top level there is the need to

manage accumulated wealth. These various levels of reasons for saving correspond to

different types of savers.

Several studies used the human needs hierarchy of Maslow (1954115

). Maslow‘s

hierarchy suggests that all needs are not of equal importance and that people will pursue

higher level needs once lower level needs are achieved. Xiao and Anderson (1993116

) and

Xiao and Olson (1993117

) incorporated Maslow‘s need hierarchy theory and the

behavioural life cycle hypothesis into their approach. They found that families show

different saving motivations and save according to different categories of mental

accounting to provide for different needs. Xiao and Noring (1994118

) claimed that

motivations for current and future consumption may be defined as financial needs and

that these reflect the human needs described by Maslow. Lower level financial needs

concern current consumption whereas those of a higher level reflect future consumption.

They maintain that when a family has many financial resources available (income, assets,

and net worth) it is more probable that it satisfies financial needs of a higher level and

their empirical work provide some support for this claim. They proposed that the families

with few resources would save to provide for daily expenses; families in middle income

or net worth groups would save for emergencies; and, families in the highest income or

114 Lindqvist, A. (1981). A note on determinants of household saving behaviour. Journal of Economic Psychology, 1(1), 39-57. 115 Maslow, A. (1954). Motivation and personality. New York: Harper and Row. 116 Xiao, J. J., & Anderson, J. G. (1993). A hierarchy of financial needs reflected by household paper assets.

In T. Mauldin (Ed.). The proceedings of the American council on consumer interests 39th annual

conference, Columbia, MO: American Council on Consumer Interests, 207–214. 117 Xiao, J. J., & Olson, G. I. (1993). Mental accounting and saving behaviour. Home Economics Research

Journal, 22(1), 92–109. 118 Xiao, J. J., & Noring, F. E. (1994). Perceived saving motives and hierarchical financial needs. Financial

Counseling and Planning, 5, 25–44.

43

net worth groups would save for retirement, children, and advancing a standard of living.

The researchers found household saving motivations are hierarchical, with daily expenses

being the basic level, emergency being the intermediate level, and retirement, children,

and advancing being the highest level. These findings were consistent with their

expectations based on Maslow‘s hierarchy.

Warneryd (1995119

) distinguished four motives for saving and stressed that a person can

save for one or more motives at the same time. He labels the first ―Saving as a continuous

habit‘‘. This is a well established habit of saving which is not related to any specific goal.

The second, the so-called ‗‗Precautionary motive‘‘, is due to uncertainty about the future.

The third motive for saving is the ‗‗Bequest motive‘‘, which is saving for the well-being

of the family after the person‘s death. The fourth and last motive is called the ‗‗Profit

motive‘‘ and consists of the wish to make an income from money put aside. The results

of a multiple regression analysis indicated that the motivations ―Saving as a continuous

habit‖ and ―Precaution‖ contribute significantly to explaining the variance of the total

sum of money saved.

Canova et al. (2005120

) studied goals that motivate the individual‘s decision to save and

represented these goals in hierarchical structure of the linkages between the goals. Fifteen

salient goals were identified and found to function hierarchically. They found that at the

bottom of hierarchy are more concrete goals (e.g. purchase, holidays or money

availability), while at the top are more abstract goals (e.g. self esteem, self gratification).

In the intermediate position are goals which channel the more concrete towards the more

abstract (p. 21, 30). In their study they found three general orientations toward the focal

goal of saving can be discerned. One of these is concerned with ways of avoiding debt

and of achieving a certain security in life. A second orientation is reflected in the desire

for self-gratification, which can be reached by means of holidays, hobbies, purchases, and

intermediaries such as looking after the family. The last orientation focuses upon thinking

119 Warneryd, K.E. (1995). A study of saving behaviour towards the end of the life cycle. Center for

Economic Research, Tilburg University, Progress Report No. 28. 120 Canova L., Rattazzi M. A. A., & Webley P. (2005). The hierarchical structure of saving motives. The

Journal of Economic Psychology. 26, 21-34.

44

about old age. For these respondents, saving for retirement is important to guarantee

gratification in this period of life. Then there are linkages among the three super ordinate

goals: security (leading to autonomy), self-esteem and self-gratification are reciprocally

connected. (p. 31).

DeVaney, Anong, and Whirl (2007121

) analyzed the likelihood of progressing to a higher

level motive after fulfilling a goal associated with a lower level saving motive. Their

proposed saving motive hierarchy went from saving for physiological or basic needs, for

safety needs, for security, for love and social needs, for esteem and luxury needs, and for

self-actualization. They added an additional level reflecting the absence of any saving.

They also found younger households tended to move from no savings, to saving for basic

needs, to saving for security. Older households were more likely to move from saving for

love or social needs, to saving for luxuries.

Public pension benefits also influence the saving behaviour of individuals. Empirical

evidence on the impact of public pension schemes on household saving has generally

been inclusive. Feldstein (1980122

) argued that ―public pension schemes have a negative

impact on private saving. Ehrlich and Zhong (1998123

) studies with a sample of 49

countries over 29 years (1960-89) and found that ―pension benefits having significant

depressing effect on savings‖ (p. 155).

Callen and Thimann (1997124

) explained that ―the overall impact of the social security

and welfare systems on individual saving behaviour is likely to be dependent on a

number of features of the systems including the value of the benefit payments (the higher

the replacement ratio –defined as the entitlement as a percentage of previous earnings-

121 Devaney, S., Anong, S., & Whirl, S. (2007). Household savings motives. Journal of Consumer Affairs,

41(1), 174-186. 122 Feldstein, M. (1980). The effect of social security on private savings: The time series evidence. NBER

Working Paper 0314, National Bureau of Economic Research, Inc. 123 Ehrlich, I. & J-G. Zhong. (1998). Social security and the real Economy: An inquiry into some

neglected issues, American Economic Review, 88(2), 151-157. 124 Challen, T. & Thimann, C. (1997). Empirical determinants of household saving: Evidemce from OECD

countris. Asia and Pecific Department. International Monetary Fund.IMF Working Paper No. WP/97/181,

1-26.

http://ideas.repec.org/p/nbr/nberwo/0314.html

45

the less incentive there is for private saving provision); the length of time over which

payments are available; the certainty with which people regard the future benefits; and

the general availability of such payments‖ (p. 8). They also found a standard

demographic impact on household saving. Result showed that with a higher old-age

dependency ratio being associated with lower household saving. The young-dependency

and overall-dependency ratios were also tested, but were not found to be significant (p.

13). NCAER (1961125

) concluded that desire for making provisions for emergencies were

a very important motive for saving for old age.

These saving motives, in turn suggest a large number of variables that may influence

household saving decisions. Among the most commonly used in empirical studies are:

growth in income, demographics, real interest rate, and inflation (Callen and Thimann,

1997126

), household wealth, unemployment (Skinner, 1988127

), terms of trade, tax

structure (Boadway and Wildasin, 1994128

) and proxies for financial deregulation

(Aghevli et al., 1990129

).

Goodfellow (2007130

) found that ―among all the determinants, stage in the life cycle is a

significant factor, influencing attitudes and behaviour of savings‖ (p. 38). He also found

that ―anticipated time horizon is the second most influencing factor for saving behaviour,

while level of saving amount the influenced by an individual‘s routine and non-routine

expenditures‖ (p. 45, 46). Belk (1974131

) found that ―differences are prevailing in the

125 National Council for Applied Economic Research & Max New York Life Insurance Company Ltd.

(2007). How India Earns, Spends and Saves: India Financial Protection Survey. Delhi: National Council

for Applied Economic Research and Max New York Life Insurance Company Ltd. Research Report. 126 Challen, T. and Thimann, C. (1997). Empirical determinants of household saving: Evidemce from

OECD countris. Asia and Pecific Department. International Monetary Fund.IMF Working Paper No.

WP/97/181, 1-26. 127 Skinner, J. (1988). Risky income, life cycle consumption and precautionary saving. Journal of Monetary

Economics, 22, 237–255. 128 Boadway, R. & Wildasin, D. (1994). Taxation and savings: A Survey. Fiscal Studies 15(3): 19-63. 129 Aghevli, B., Boughton, J., Montiel, P., Villanueva, D., & Woglom, G., (1990). The role of national

saving in the world economy. Occasional Paper, 67. Wasnigton, D.C. International Monetary Fund. 130 Goodfellow, J. H. (2007). Consumer perceptions and attitudes towards savings and investments.

International Journal of Bank Marketin, 5(3), 32-48. 131 Belk, R., (1974). An exploratory assessment of situational effects in buyer behaviour. Journal of

Marketing Research, 156-163.

46

preferences between the individuals is due to the fact that choices are situation specific

and that different individuals may give their preferences with varying context‖.

The development in financial system has increased the opportunities for, and returns to,

financial saving, but it may also enhance access to credit and ease liquidity constraints

faced by households and could, therefore, at least initially, lead to lower household

saving.

As a result of privatization, liberalization and deregulation, financial services industry is

characterized by an intense competition not only within traditional banking institutions,

but also with other non banking financial firms, this intensified competition brings the

critical importance of understanding consumer decision making to the financial services

industry‘s attention.

2.5 Investment Decision Making and Irrationality

As discussed in previous section, theories of behavioural finance and behavioural

economics assume that people make irrational decision. These theories are increasingly

questioning the notion of absolute rationality. Rationality itself is bound by context and

directed to personal and community ends. There is no one rational outcome for every

financial decision.

Decision making can be defined as the process of choosing a particular alternative from a

number of alternatives. It is an activity that follows after proper evaluation of all the

alternatives. Karlsson et al., (2004132

) said that ―Individuals make decisions with regard

to their personal finances on a daily basis, and even though these decisions are necessary

for day-to-day survival, it can be a daunting task‖ (p. 754). The value associated with

analysis of the consumer decision making process is widely recognized by various

researchers.

132 Karlsson, N., Dellgran, P., Klingander, B. and Gärling, T. (2004). Household consumption: Influences

of aspiration level, social comparison, and money management. Journal of Economic Psychology, 25(6),

753– 769.

47

Previous research in the area of consumer behaviour and financial services has revealed

that lifecycle stages, age, education, gender and income are important factors to consider

when seeking to understand the needs and wants of customers (Gerrans and Clark-

Murphy, 2004133

; Gough and Sozou, 2005134

) and the type of financial product or service

being purchased greatly influences the consumers‘ purchasing behaviour (Beckett et al.,

2000135

; Howcroft et al., 2003136

).

There is evident that individual‘s choice of decision is found to be influenced by the

following factors: decision making complexity (Bettman and Park, 1980137

; Johnson et

al., 1989138

) time pressure (Wright and Weitz, 1977139

), product knowledge and

experience (Lee and Geistfeld, 1998140

; Moore and Lehman, 1980141

), involvement and

need for cognition (Mantel and Kardes, 1999142

), socio economic status (Capon and

133 Clark-Murphy, M. & Gerrans, P. (2002). Women‘s ‗problems‘ with finance and investment: a result of

gender differences in information processing? Paper presented at the 11th International Women in

Leadership Conference, Perth. 134 Gough, O. & Sozou, P.D. (2005). Pensions and retirement savings: cluster analysis of consumer

behaviour and attitudes. International Journal of Bank Marketing, 23(7), 558-570. 135 Beckett, A., Hewer, P. & Howcroft, B. (2000). An exposition of consumer behaviour in the financial services industry. International Journal of Bank Marketing, 18(1), 15-26. 136

Howcroft, B., Hewer, P. & Hamilton, R. (2003). Consumer decision-making styles and the purchase of

financial services. The Service Industries Journal,(23)3, 63-81. 137 Bettman, J. R. & Park, C. W. (1980). Effects of prior knowledge and experience and phase of the choice

process on consumer decision processes: a protocol analysis. Journal of Consumer Research, 7(2), 234-

248. 138 Johnson, E. J., Meyer, R. J. & Ghose, S. (1989). When choice models fall: compensatory models in

negatively correlated environments. Journal of Marketing Research, 26, 255-270. 139 Wright, P. & Weitz, B. (1977). The relationship between Luce‘s choice axiom, Thurstone‘s theory of

comparative judgement and the double exponential distribution. Journal of Mathematical Psychology, 15,

109-144. 140 Lee, J. & Geistfeld, L. V. (1998). Enhancing consumer choice: are we making appropriate recommendations?. Jounal of Consumer Affairs, 32(2), 252-274. 141 Moore, W. L. & Lehmann, D. (1980). Individual differences in search behaviour for a non-durable.

Journal of Consumer Research, 7, 296-307. 142 Mantel, S. P. & Kardes, F. R. (1999). The role of direction of comparison, attribute-based processing,

and attitude-based processing in consumer preference. Journal of Consumer Research, 25(3), 335-352.

48

Burke, 1980143

; Lee and Geistfied, 1998144

), and demographics (Darley and Smith,

1995145

) and various sources of information (Chandra et al., 2011146

).

With regard to factors influencing individual investors‘ decision making, Baker and

Haslem (1974147

) contended that dividends, expected returns and firm‘s financial stability

are critical investment considerations for individual investors. Merikas et al. (2003148

)

studied 26 economic variables that affect the individual investors in Greece. They did not

rely on single integrated approach, but rather on many categories of factors such as

‗accounting information‘, ‗subjective/ personal‘, ‗neutral information‘, ‗advocate

recommendation‘, and ‗personal financial needs‘. This study found that Accounting

information that includes, condition of financial statements, expected corporate earnings,

expected dividends, firm‘s status in industry, affordable share price, past performance

firm are the most influencing factors on investment decision of investors. This study also

found that environmental criteria such as, ‗coverage in press‘, ‗statement from politicians

and government officials‘, ‗ease of obtaining borrowed funds‘ and ‗political party

affiliation‘ are the least important for individual investors.

Nagy and Obenberger (1994149

) examined factors influencing investors‘ behaviour. They

studied 34 variables such as expected corporate earnings, diversification needs, feeling

for firm‘s products and services, past performance of the firm, broker/ advisor/ analyst‘ s

recommendation to a name few. The findings suggest that the classical wealth

maximization criteria are important for investors. Contemporary concerns such as local

143 Capon, N. &Burke, M. (1980). Individual product class, and task related factors in consumer

information processing. Journal of Consumer Research, 7(3), 314-326. 144 Lee, J. & Geistfeld, L. V. (1998). Enhancing consumer choice: are we making appropriate

recommendations?. Jounal of Consumer Affairs, 32(2), 252-274. 145 Darley, W. K. & Smith, R. E. (1995). Gender differences in information-processing strategies: an

empirical test of the selectivity model in advertising response. Journal of Advertising, 24 (1), 44-56. 146 Chandra, A. & Kumar, R. (2011). Determinants of individual investor behaviour: An orthogonal linear

transformation approach. Munich Personal RePEc Archive No. 29722, accessed on April 15, 2011 at

http://mpra.ub.uni-muenchen.de/29722/ 147 Baker, H., & Haslem, J. (1974). Toward the development of client-specified valuation models. Journal

of Finance, 29 (4), 1255-1263. 148 Merikas, A. A., Merikas, A. G, Vozikis, G. S. & Prasad, D. (2003). Factors influencing Greek Investor

behaviour on the Athens stock exchange. Journal of Applied Business Research, 20 (4), 93-99. 149 Nagy, R. A. & Obenberger, R. W. (1994). Factors affecting investors‘ behaviour. Financial Analyst

Journal, 50, 63-68.

http://mpra.ub.uni-muenchen.de/29722/

49

and international operations, environmental track record, and firm‘s ethical posture

appear to be given only cursory considerations.

Hodge (2003150

) analyzed the investors‘ perceptions of earning quality, auditor

independence, and the usefulness of audited financial information. This study concluded

that lower perceptions of earning quality are associated with greater reliance on a firm‘s

audited financial statements and fundamental analysis of those statements when making

investment decisions.

Benston et al. (2006151

) concluded that investors require a substantial amount of

information that goes beyond financial accounting numbers. They also require

information about ―current and expected changes in market conditions, competitors‘

products and performance, the potential value of new products and processes, prospective

changes in foreign exchange value and domestic inflation rates, government policies,

employee and customer relations, and the quality of management‖.

Draft Green Paper on Consumer Policy Framework (DTI) (2004152

) states that more and

more consumers are interested in the world behind the products, the production process

and the ethics of the company that produces goods and services. Blumberg et al.

(1997153

) added that the stakeholders are always interested to the extent to which the

company is investing in social and related issues. They always want to see company as a

going concern. Epstein (1994154

) examined the demand for social information by

individual investors. The results of this study indicate a strong demand for information

about the product safety and quality, and about the company‘s environmental activities.

150 Hodge, F. D. (2003). Investors‘ perceptions of earning quality, auditor independence, and usefulness of

audited financial information. Accounting, Horizons, 17, 37-48. 151

Benston, G. J., Bromwich, M. & Wagenhofer, A. (2006). Principles-versus rules-based accounting

standards: the FASB‘s standard setting strategy. ABACUS, A Journal of Accounting, Finance and Business

Studies, 42 (2), 165-188. 152

Government Gazette (2004). Draft Green Paper on Consumer Policy Framework. Republic of South

Africa, 471 (9), September 9, 2004, Pretoria. 153

Blumberg, J., Korswold, A. & Blum G. (1996). Environmental Performance and Shareholder Value

.World Business Council for Sustainable Development: Geneva. 154 Epstein, M. J. (1994). Social disclosure and the individual investor. Accounting, Auditing and

Accountability Journal, 4, 94-109.

50

Furthermore, a majority of the investors surveyed also want the company to report on

corporate ethics, employee relations and community involvement.

Chandra et al. (2011155

) explained that not only professional and contextual sources of

information, which include stock brokers, financial consultants and investment advisors,

but also contextual factors such as, market share and reputation of the firm, accounting

and financial information, publicly available information through various media,

advocate recommendation that of brokers, family and friends and personal financial need

influence the investment decision of investors. They also found that investors also follow

technical analysis, fundamentals (accounting and financial information) and market share

of a company while investing.

Hussein et al. (2009156

) also indentified 37 variables influencing investment decision of

UAE investors. This study categorized 37 variables into eight groups. Eight variables

corresponding to self-image/ firm image coincidence, eleven variables corresponding to

accounting information, six variables corresponding to neutral information, five variables

to advocate recommendation, and seven variables to personal financial needs. SEBI and

NCAER (2011157

) reported that safety and liquidity were the primary considerations

which determined the choice of asset to invest in.

Literature also establishes relation between individuals‘ demographic and socio-

economic variables and behavioural finance related to investment decision. There is

evidence that women are less confident (Clark-Murphy and Gerrens, 2002158

; Taylor,

2003159

) and less knowledgeable (Chen and Volpe, 1998160

) than men on the topics of

155

Chandra, A. & Kumar, R. (2011). Determinants of individual investor behaviour: An orthogonal linear


http://mpra.ub.uni-muenchen.de/29722/ 156 Hussein A. Hassan Al-Tamimi & Al Anood Bin Kalli (2009). Financial literacy and investment

decisions of UAE investors. The Journal of Finance, 10(5), 500- 516. 157 Securities and Exchange Board of India and National Council of Applied Economic Research (2000).

How Households Save and Invest: Evidence from NCAER Household Survey. New Delhi. 158 Clark-Murphy, M. & Gerrans, P. (2002). Women‘s ‗problems‘ with finance and investment: A result of

gender differences in information processing Paper presented at the 11th International Women in

Leadership Conference, Perth. 159 Taylor, P. (2003). Gender gap creates niche in financial services. Financial News, 8 March, p. 24.


51

personal finance. Males generally exhibit more confidence in dealing with financial

affairs (Taylor, 2003161

), whereas ―women are more conservative in their investment

practices‖ (Bajtelsmit, V. and Bernasek, 1996162

). Age is another demographic factor that

affects investment decision of investors examined the older investors (Korniotis and

Kumar, 2011163

). Harrison (2003164

) suggested, the past investment experience and

expertise often influence the investors‘ decision with regard to purchase of financial

products. Lewellen et al. (1977165

) suggested, investors with lower age, young, higher

level of income, higher level of education, and less family members choose to invest their

money in risky assets than conservative instruments.

The behavioural finance suggests that investment decision is only influenced by the

demographics and socioeconomic variables, but also by risk tolerance capacity and

amount of financial information available with the investor, as well as his/her information

processing capacity to analyze the environmental set. In the next section, the discussion

on the association between 1) risk tolerance and decision making and 2) financial

information and investment decision making of investors is presented through in-depth

review of literature.

2.5.1 Risk Tolerance and Investment Decision Making

Risk tolerance is an important concept that has a direct and obvious link with the

investment decision-making process. The number of factors have been studied, proposed

and tested as determinants of risk tolerance.

160 Chen, H. & Volpe, R. P. (1998). An analysis of personal financial literacy among college students.

Financial Services Review, 7 (2), 107-128. 161 Taylor, P. (2003). Gender gap creates niche in financial services. Financial News, 8 March, p. 24. 162 Bajtelsmit, V. & Bernasek, A. (1996). Why do women invest differently than men? Journal of Financial

Counseling and Investing, 7, 1-10. 163 Kornitiotis, G. M. & Kumar, A. (2011). Do older investors make better investment decisions? Review of Economics and Statistics, 93 (1), 244-245. 164 Harrison. (2003). Understanding the behavior of financial services consumers: A research agenda.

Journal of Financial Services Marketing, 8 (1), pp. 6-9. 165 Lewellen, W., Lease, R. & Schlarbaum G. (1997). Pattern of investment strategy and behaviour among

individual investors. The Journal of Business, 50, 296-333.

52

With respect to age and risk-tolerance ability, previous studies found that the risk

tolerance decreases with the age (Wallech & Kogan, 1961166

; Palsson, 1996167

), although

the studies also concluded that this relationship may not be necessarily linear (Riley &

Chow, 1992168

; Bajelsmit & VanDerhei, 1997169

). In fact, the reality can be explained by

the fact that younger investors have a greater number of years to recover from the losses

that may be incurred with the risky investments.

However, the issue of gender and risk-taking ability is complex. Bajtelsmit and Bernasek

(1996170

) suggest that gender risk differences ―have their root in discrimination and/or

differences in individual preferences‖ (p. 5). Similarly, the Gerrans and Clark-Murphy

(2004171

) found ―the gender effect is not uniform and can be demonstrated as depending

on marital status, whether the member considered themselves informed and age‖ (p. 27).

The studies have shown that the single women are more risk averse (Bajtelsmit et al.,

1999172

; Gerrans and Clark-Murphy, 2004173

) than single men or married couples (Sung

and Hanna, 1996174

). While another group of researchers and financial practitioners have

suggested that women choose to invest their financial resources more conservatively and

166 Wallach, M. A. & Kogan, N. (1961.) Aspects of judgment and decision making: Interrelationships and

changes with age. Behavioural Science, 6, 23- 26. 167 Palsson, A.M. (1996). Does the Degree of Relative Risk Aversion Vary with Household Characteristics?

Journal of Economic Psychology, 17, 771 – 787. 168

Riley, W.B., & Chow, K.V. (1992). Asset al.location and Individual Risk Aversion, Financial Analysts

Journal, 48, 32 – 37. 169

Bajtelsmit, V.L. & VanDerhai, J.L. (1997). Risk Aversion and Pension Investment Choices. In O.S.

Mitchell, (ed), Positioning Pensions for the Year 2000. Philadelphia, PA: University of Pennsylvania Press. 170 Bajtelsmit, V.L. and Bernasek, A. (1996). Why do women invest differently than men? Journal of

Association for Financial Counseling and Planning Education, 7, 1-10. 171 Gerrans, P. & Clark-Murphy, M. (2004). Gender differences in retirement savings decisions. Research

paper, Edith Cowan University, Perth, p. 29. 172 Bajtelsmit, V.L., Bernasek, A. and Jianakoplos, N.A. (1999). Gender differences in defined contribution pension decisions. Financial Services Review, 8(1), 1-10. 173 Gerrans, P. & Clark-Murphy, M. (2004). Gender differences in retirement savings decisions. Research

paper, Edith Cowan University, Perth, p. 29. 174 Sung, J. & Hanna, S. (1996). Factors related to risk tolerance. Financial Counseling and Planning, 7,

11-20.

53

are generally more risk averse than men (Bajtelsmit & VanDerhei, 1997175

; Yuh &

Hanna, 1997176

).

Contrary to these findings, Grable and Joo (1999177

) did not find gender to be a

significant predictor of an individual‘s risk tolerance level. Furthermore, Embrey and Fox

(1997178

) examined gender differences in the investment decision making process and

found that women were more risk averse than men. Based on the Survey of Consumer

Finances (SCF, 1997179

) measure of risk tolerance but that gender did not influence

investment choice; more specifically, it was found that ―differences in purely financial

investment decisions between men and women appeared to be more a result of

differences in wealth as measured by net worth and the expectation of an inheritance‖ (p.

38). Sung and Hunna (1996180

) have found that education is also an important factor to

evaluate the risk- tolerance ability of an individual.

The amount and nature of perceived risk define consumers‘ information needs.

Accordingly, consumers search for the sources, types, and amounts of information that

seems most likely to satisfy their particular information needs. Thus, information search

as a strategy of risk reduction in the face of risk in the investment decision making

process. The following section explains the importance of financial information in

investment decision making.

2.5.2 Financial Information and Investment Decision Making

175 Bajtelsmit, V.L. & VanDerhei, J.A. (1997). Risk aversion and retirement income adequacy. Positioning

pensions for the twenty-first century. Michael S. Gordon, Olivia S. Mitchell, Marc M. Twinney, Eds.

Philadelphia: University of Pennsylvania Press. 176 Yuh, Y. & Hanna, S. (1997). The Demand for Risky Assets in Retirement Portfolios. Proceedings of the

Academy of Financial Services. 177 Grable, J. & Joo, S. (1999). Factors related to risk tolerance: a further examination.,

Consumer interests annual, 45, 53-58. 178 Embrey, L. C., & Fox, J. J. (1997). Gender differences in the investment decision-making process.

Financial Counseling and Planning, 8(2), 33-40. 179 Kennickell, A.B. (1997). Codebook for 1995 Survey of Consumer Finances. Federal Reserve System,

Washington, D.C. 180 Sung, J. & Hanna, S. (1996). Factors related to risk tolerance. Financial Counseling and Planning, 7,

11-20.

54

The decision-making for investment products can be described within the framework of

consumer purchase decision-making, which is depicted as a series of steps that include

problem recognition, information search, evaluation of alternatives, purchase decision,

and post-purchase behaviour (Schmidt & Spreng, 1996181

). Under this framework,

information search is one of the critical elements of consumer decision-making (Moore &

Lehmann, 1980182

).

Individuals make decisions with regard to their personal finances on a daily basis.

Investment generally involves substantial amount of money and risk, and information

search is therefore an important activity for many consumers before making investment

decisions. This is especially true for long-term financial decisions, such as retirement

planning (Bernheim and Garrett, 2003183

). However, they suggested that consumers not

only need information, they want information on relevant products and services for

retirement. Previous studies found that consumer expertise and knowledge are important

to the decision-making process for the purchase of financial products or services and

consumer knowledge also influences financial behaviour (Howcroft et al., 2003184

). Thus,

financial knowledge and money-management skills are crucial for making good financial

decisions. Lusardi and Mitchell (2006, 2007a, 2008) also found that the least literate are

also the least likely to plan and save for retirement. Kim (2007185

) found that

―excessively high debt levels, low saving rates, becoming targets of investment fraud,

delinquency on credit cards and bankruptcy have all been found to be related to financial

illiteracy in individuals‖ (p. 1). Kim (2007186

) and Joo (1998187

) found that ―adults lack

the financial knowledge to make competent and effective financial choices‖. Lusardi and

181 Schmidt, J. B. & Spreng, A. R. (1996). A proposed mode of external consumer information search.

Journal of theAcademy of Marketing Science, 23 (Winter), 57-65. 182

Moore, W., & Lehmann, D. (1980). Individual differences in search behavior of nondurable. Journal of

Consumer Reseaerch, 7 (December), 296-307. 183 Bernheim, B. D., & Garrett, D. M. (2003). The effects of financial education in the workplace: Evidence

from a survey of households. Journal of Public Economics, 87(7-8), 1487-1519. 184 Howcroft, B., Hewer, P. & Hamilton, R. (2003). Consumer decision-making styles and the purchase of

financial services. The Service Industries Journal, 23 (3), 63-81 185 Kim, J. (2007). Workplace financial education program: Does it have an impact on employees' personal

finances? Journal of Family and Consumer Science, 99 (1), 43-47. 186 Ibid 187 Joo, S. (1998). Personal financial wellness and worker job productivity. Unpublished Ph.D. thesis.

Blacksburg: Virginia Polytechnic and State University.

55

Mitchell (2007188

) found that financially unsophisticated households tend to avoid the

stock market investments‖ (p.19) On the subject of risk, there is clear evidence to show

that services have a higher degree of perceived risk when compared directly with goods

(Murray, 1991189

; Zeithaml et al., 1985190

) which directly and positively correlates to

information search and purchasing decision. That is, the greater the perceived risk, the

greater the information search (Turley and LeBlanc, 1993191

), and the subsequent delay in

making a purchasing decision. In the literature, there is a consensus, both conceptually

and empirically, that a higher level of perceived risk in a pre-purchase context increases

consumers‘ propensity to seek information about a product or service (Dowling and

Staelin, 1994192

). Abdelkarim, et al. (2009193

) said that the financial information is

supposed to facilitate the prediction of firm‘s future cash flows and help the investors to

assess the future securities risk and return; hence performance forecast should be crux of

the financial information (p. 47).

The importance of information in the pre-purchase decision-making process for the

consumers of financial product and/or services has also been established (Friedman and

Smith, 1993194

). However, Schmidt and Spreng‘s (1996195

) model suggests, while making

investment decisions, consumers‘ information search (behaviour) depends on their

motivation to search and their ability to search, none of these studies ranked personal

information sources. Lin (2002196

) suggests investors collect financial information from

188 Lusardi, Annamaria & Olivia S. Mitchell (2007a). Financial Literacy and Retirement Preparedness:

Evidence and Implications for Financial Education. Business Economics, January 2007, 35-44. 189 Murray, K. (1991). A test of services marketing theory: consumer information acquisition activities. Journal of Marketing, 55 (1), 10-25. 190 Zeithaml, V.A., Parasuraman, A. &Berry, L.L. (1985). Problems and strategies in services marketing.

Journal of Marketing, 49 (2), 33-46. 191 Turley, L.W. & LeBlanc, R.P. (1993). An exploratory investigation of consumer decision making in the

service sector. Journal of Services Marketing, 7(4), 11-18. 192 Dowling, G. R. &Staelin, R. (1994). A model of perceived risk and intended risk-handling activity,

Journal of Consumer Research, 21 (June), 119-134. 193 Abdelkarim, N., Shahin, Y., & Arqawi, B. (2009). Investor perception of information disclosed in

financial reports of Palestine securities exchange listed companies. Accounting and Taxation, 1 (1), p. 45-

61. 194 Friedman, M.L. & Smith, L.J. (1993). Consumer evaluation processes in a service setting. Journal of

Services Marketing, 7(2), 47-61. 195

Schmidt, J. B. &Spreng, A. R. (1996). A proposed mode of external consumer information search.

Journal of theAcademy of Marketing Science, 23 (Winter), 57-65. 196 Lin (2002). Consumer’ information search when making investment decisions. (Doctoral thesis,

University of Georgia, Athens, Georgea, 2002).

56

personal as well as impersonal sources. Personal sources include professional financial

services providers (brokers, financial planners, and other professionals), friends/relatives,

experienced investors, and third party agents. Impersonal sources include written material

(e.g. books, brochures, reports, magazines), media (e.g. TV, radio programs), and the

Internet. The literature evident that family is a particularly credible source considered to

be more trustworthy than friends or professional advisors such as accountants or financial

planners. In addition participants mentioned that seeing a relevant television segment, or

reading a relevant newspaper article or listening to a relevant radio program had

prompted them to give some thought to their long-term financial future.

Arlen et al. (2007197

) emphasized that due to lack of confidence, investors heavily rely on

financial advice. Sung and Sandager (1997198

) examined the characteristics of the

consumers, who need certified financial planners. This study found that potential

investors want financial advice particularly on retirement planning, investment planning,

and tax planning and they prefer a certified financial planner to be affiliated with an

independent financial firm. Krishnan and Brooker (2002199

) found that investors use

analyst‘s recommendation while investing. Nagy and Obenberger (1994200

) found that the

recommendation of brokerage houses, individual stock brokers, family members and co-

workers (colleagues) go largely unheeded.

Lee and Hogarth (2002b201

) and Capon and Lutz (1979202

) condensed consumer

information sources into three principal clusters that effectively espoused most of the

perspectives articulated in the other studies. These are: 1) Personal Sources, which

197 Arlen, C. Ponston, L. R. & Akbulut, A. Y. (2007). Advice availability and gender differences in risky

decision making: A study of online retirement planning. Proceedings of the 40th Hawai International

Conference on System Sciences. 198 Sung, B. C. & Sandager, J. P. (1997). What consumers look for in financial planners? Association for

Financial Counseling and Planning Education. 199 Krishnan, R. & Brooker, D. M. (2002). Investors use of analysts‘ recommendations. Behavioural

Research in Accounting, 14, 129-158. 200

Nagy, R. A. & Obenberger, R. W. (1994). Factors affecting investors behaviour. Financial Analyst

Journal, 50, 63-68. 201

Lee, J. & Hogarth, J. M. (2000b). Relationships among information search activities when shopping for

a credit card. The Journal of Consumer Affairs, 34 (2), 330-360. 202 Capon, N. & Lutz, R. (1979). A model and methodology for the development of consumer information

programs. Journal of Marketing, 43 (1), 58-67.

57

largely take form of the informal inquires with personal contacts, for instances friends,

relatives, neighbours, acquaintances, co-workers and peers. 2) Independent Sources,

which encompass various neutral agencies and levels of government, independent rating

agencies and organizations that certify the quality of products and firms, and 3)

Commercial Sources, which include all entities that have a direct economic interest in an

product and include manufacturers, retailers and trade associations.

Toussaint- Comeau (2002203

) using the data from a household survey conducted in

Chicago, found that socio-economic, demographic and life style characteristics affect

consumers‘ preferences as to receipt of financial information. They found, households

with lower income, less educated are less likely to select internet as means of finding

information about personal financial issues, but more likely to prefer formal courses

offered in the local community. Low-income and minority consumers are also more

likely to select radio programmes as a means of receiving information about financial

issues; while, older adults are more likely to choose seminars to receive financial

information. Hogarth and Hilgert et al. (2003204

) asked the respondents about preferred

sources of information on financial topics. They found that more financially sophisticated

consumers prefer internet. In general, however, households prefer to receive financial

information through media sources such as television, radio, magazines and newspapers

as well as through informational videos and brochures.

Nick et al. (2010205

) surveyed respondents to know consumer decision making in retail

services with regard to information search. This study found that various information

sources such as, websites, telephone representatives of a company, newspapers/

magazines, family members, friends, financial professionals, television, formal study,

consumer advice organizations are those who are employed in financial services industry

are more likely to be used for creating/ enhancing background financial knowledge than

203 Toussaint-Comeau, M. (2002). Delivery of financial literacy programs. The Journal of Consumer

Education, 19 (20). 204 Hilgert, M.A., Hogarth, J.M. and Beverly, S.G. (2003) Household financial management: The

connection between knowledge and behaviour. Federal Reserve Bulletin, 89 (July): 309-322.Washinton,

D.C. 205 Nick, C., Huck, S. & Inderest, R. (2010). Consumer Decision-Making in Retail Investment Services: A

Behavioural Economics Perspective. Decision Technology Ltd.

58

searching for available investment options. Bennett and Harrell (1975206

) and Howard

and Sheth (1969207

) also found that reduction of risk is a major benefit of information

search.

With reference to gender, a number of research studies support notion that women more

comprehensively process the information than do men in the same task context

(Banyamini et al., 2000208

; Graham, 1994209

). Taylor (2003210

) found that the males

generally exhibit more confidence when dealing with their financial affairs. Bajtelsmit

and Bernasek (1996211

) found that women to be more conservative in their investment

practices. Clark-Murphy and Gerrans (2002212

) found that men and women are simply

process information differently. Their risk profiles and confidence levels are different on

the subject of finances. The impact of information on investment decision making has

two separate dimensions to it. Women may differ in access to information and they may

also differ in their ability or inclination to use available information.

The lens model approach, also known as the Brunswik lens model, uses a set of explicit

cues from environment to assess the situations in which decision makers make

judgments. 1) The environmental criteria and the information set, which explains, the

environmental changes impact on the way in which information is processed. Hence,

Decision makers need to be aware of environmental changes and their effect on

information and 2) The information set and subject responses, which explains, the

decision makers‘ response to the available information is dependent on their cognitive

ability and knowledge of subject matter.

206 Benett, P. D. & Harrell, G. D. (1975). The role of confidence in understanding and predicting buyers‘

attitude and purchase intentions. Jourrnal of Consumer Research, 2, 110-117. 207

Howard, J. & Sheth, J. (1969). The Theory of Buyer Behaviour. John Wiley & Sons. New York. 208 Banyamini, Y., Leventhal, E. & Levanthal, H. (2000). Gender differences in processing information for

making self-assessments of health. Psychosomatic Medicine, 63(3), 354-394. 209 Graham, J. (1994), Marketing communication receivers‘ perception of source-self similarity: some new

findings. Journal of Marketing Theory and Practice, 2(4), 11-19. 210 Taylor, P. (2003). Gender gap creates niche in financial services. Financial News, 8 March, p. 24. 211 Bajtelsmit, V. & Bernasek, A. (1996). Why do women invest differently than men? Journal of Financial

Counseling and Investing, 7, 1-10. 212 Clark-Murphy, M. &Gerrans, P. (2002). Women‘s ‗problems‘ with finance and investment: a result of

gender differences in information processing?. paper presented at the 11th International Women in

Leadership Conference, Perth.

59

Accordingly, investors tend to engage in more extensive search activities while

purchasing products that are more expensive or carry more risk. By searching for

information, investors may find products with greater benefits that may enhance their

satisfaction with the products and/or the decisions and/or reduce the risk associated with

those.

2.6 Conclusion

From above discussion, it can be concluded that in the financial markets investors are

distinguished by extent of their activity, demographics and socio economic profiles,

saving motives, risk tolerance capacity, their motivation and ability to search the financial

information and to process the same for making investment decision, which in turn also

gets influenced by other variables. In this whole process, level of their sophistication (that

investors possess), among other things, also plays a crucial role. In the literature, this

level of sophistication also refers as ―level of financial literacy‖.

Financial Literacy

and

Financial Behaviour

Part II

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2.7 Introduction

2.8 Global Scenario: International Studies on Financial Literacy

2.8.1 U.K. Studies

2.8.2 U.S. Studies

2.8.3 Australian Studies

2.8.4 Singapore Study

2.8.5 OECD Studies

2.9 Domestic Scenario

2.9.1 India Protection Survey - How India Earns, Spends and Saves

2.9.2 Financial Literacy and domestic Regulatory Authority

2.10 Theoretical Framework for Financial Behaviour

2.10.1 Goal Setting Theory

2.10.2 Human Ecological Model

2.10.3 Family Management Systems

2.10.4 Discounted Utility Model

2.10.5 Life Cycle Hypothesis of Saving

2.10.6 Behavioural Life Cycle Hypothesis

2.10.7 Maslow‟s Need Hierarchy Theory

2.10.8 Theory of Reasoned Action and Theory of Planned Behaviour

2.10.9 Transtheoretical Model of Behaviour Change

2.10.10 Myers brigg‟s Type Indicator

2.10.11 Temperament Theory

2.11 Studies on Financial Literacy and Financial Behaviour

2.12 Conclusion

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2.7 Introduction

The definition of financial literacy began in the UK from National Foundation for

Education Research and was initially adopted across the UK with a view to achieve

international consistency (Noctor, Stoney and Strandling, 1992). Since then, financial

literacy has become a prominent research topic in other developed countries, where this

definition has been widely accepted and adopted by many studies. This part of the

chapter is divided into three sections. The first section presents the international studies

conducted for measuring the financial literacy of citizens of various countries such as,

The United States, The United Kingdom, Australia, Singapore and other OECD member

countries. This section also briefs the efforts made in India in the field of financial

literacy. The second section of this chapter discusses on theoretical framework for

financial behaviour. As personal finance and/or financial behaviour is based on the

theories from several disciplines such as family studies, economics, psychology and

sociology. In the third section, review of literature is presented on various studies those

have attempted to establish the relationship between financial education, financial

literacy and various financial behaviour.

2.8 Global Scenario: International Studies on Financial Literacy

2.8.1 U.K. Studies

2.8.1.1 Schagen and Lines (1996213)

Schagen and Lines (1996) conducted a financial literacy survey of the general population

on behalf of the NatWest Group Charitable Trust, with a particular focus on four groups:

young people in work or training (having age of 16 to 21 years ), students in higher

education living from home, single parents and families living in subsidized housing. The

survey questions focused on the respondents‘ attitudes to save and borrow, their use of

213 Schagen, S. & Lines, A. (1996). Financial literacy in adult life: a report to the Natwest Group

Charitable Trust, Slough, Berkshire: National Foundation for Educational Research.

62

financial information and institutions, money management in families and their

confidence in dealing with financial issues. The survey had also covered the questions

that tested respondents‘ understanding and knowledge of financial markets, financial

instruments, financial decision making, financial problem solving and financial planning.

The results had indicated that, most respondents were confident in their financial

dealings. The notable exceptions were single parents, who were less committed to

savings, and students, who were the least confident group while dealing with the financial

matters, with very few keeping any financial records.

2.8.1.2 The Adult Financial Literacy Advisory Group (AdFLAG) (2000214)

The Adult Financial Literacy Advisory Group had undertaken a study to determine ―how

to promote better access to financial education to young people and adults‖ (p. 10) by

conducting the relevant research, investigating areas of good practice, consulting with a

variety of organization across the public, private and voluntary sectors and visiting

organizations active in providing financial education programs to socially excluded

people.

The study concluded that the need for financial literacy would continue to grow because

individuals were expected to become more self-reliant, difficulties arising from changing

work patterns, an ageing population, less government involvement and increasingly

complex financial products. To this end, The Adult Financial Advisory Group

recommended that short term financial literacy education should be built around the

education, employment, housing, financial services and communication with particular

focus on needy population sectors such as older people, young people, single parents, and

people with disabilities and people living in social housing.

2.8.2 U.S. Studies

214 UK Adult Financial Literacy Advisory Group (2000), Report to the Secretary of State for Education and

Employment, December 2000

http://www.dfes.gov.uk/adflag/Adflag_-_Final_Report_.doc



63

2.8.2.1 Chen and Volpe (1998215)

Chen and Volpe (1998) conducted a survey of 924 college students from thirteen colleges

to examine their personal financial literacy; the relationship between financial literacy

and students‘ characteristics and impact of financial literacy on students‘ opinions and

decisions. The survey attempted to examine the personal financial literacy of the U.S.

college students across four main areas: general knowledge, savings and borrowings,

insurance and investments. Chen and Volpe (1998) used Analysis of Variance (ANOVA)

technique to show the variations in the levels of financial literacy among subgroups of

students. In addition, logistic regression models were used to examine the financial

literacy levels of students across different demographic characteristics. The participants

were classified into two subgroups using the median percentage of correct answers.

Students with scores higher than the median were classified as having relatively more

knowledge and students with scores equal to or below the median were classified as

having relatively less knowledge. This dichotomous variable was used as the dependent

variable in the logistic model and the independent variable were represented by the

demographic characteristic variables.

This study found that personal finance skills and knowledge are inadequate; with the

overall median percentage of correct scores was 55.56 percent. Results of the survey

showed that the most poorly answered questions were those involving investments, while

the best answered questions were those on general knowledge. The demographic

variables that were used in the analysis of the study were academic discipline, class rank,

gender, race, nationality, years of work experience, age and income. It was found that

those students with a non-business majors, women, students in a lower class rank, under

the age of 30 and had little work experience have lower levels of knowledge. It was also

found that the participants with better financial knowledge identified more efficient

options, while in their decision making concerning personal financial issues, they reacted

more effectively. This study concluded that students with less knowledge were more

215 Chen, H. & Volpe, R. P., (1998). An analysis of personal financial literacy among college students.

Financial Services Review , 7 (2), 107-128.

64

likely to hold wrong opinions and make incorrect financial decisions and college students

are not knowledgeable about personal finance. The low level of knowledge will limit

their ability to make informed decisions. The study also concluded that the level of an

individual‘s financial knowledge tends to influence attitudes that in turn affect the

individual‘s financial behaviour.

2.8.2.2 Volpe et al. (2002216)

In extension of the previous study (Volpe and Chen, 1998), they surveyed 530 online

investors to examine their investment literacy (financial literacy) and the relationship

between the literacy and online investor characteristics (e.g. education, gender investing

experience and other factors). In this study, their respondents were online investors as the

advent of online investing has significantly impacted an investor‘s decision making

process by providing instant access to a vast amount of financial information, lower

transaction costs, and quick order execution. The survey included the questions based on

investment concepts like: effect of distribution from a mutual fund on its net asset value

(NAV), blue chip stock terminology, compounding of interest, beta as a volatility

measure, capital gain tax rate, portfolio diversification, stock splits, financial ratio

analysis, appropriate asset al.location strategies, and the relationship between interest

rates and bond prices. The survey was conducted online. The results of the study found

that online investors answered about 50 percent of the questions correctly. Investors with

50 years of age or older were more knowledgeable than those who were younger and it

was consistent with those found in previous research (Volpe and Chen, 1998). Women

had lower level of investment knowledge than men. Investors with graduate degrees were

more knowledgeable than those with some high school or college education and those

who have traded online were more knowledgeable than those who have not. The overall

study concluded that the online investors‘ knowledge of investments is insufficient and

needs to be improved in the future.

216 Volpe, R. P., Kotel, J. E. & Chen, H. (2002). A survey of investment literacy among online investors.

Financial Counseling and Planning, 13(1), 1-13.

65

2.8.2.3 Moore (2003217)

The Washington State Department of Financial Institute (DFI) established and

commissioned the Social and Economic Sciences Research Centre (SESRC) at the

Washington State University to conduct a financial literacy study to investigate financial

knowledge, behaviour, attitudes and experiences. The study focused basically on two

groups: consumers who had borrowed from a lender that recently settled in a large

predatory lending case (labeled the victim pool); and the general population (labeled the

general pool).

A telephonic survey was conducted on a 1,483 adults (891 from the victim pool and 592

from the general pool). In addition to the survey, 31 participants from the victim pool

were randomly chosen to take part in four focus group sessions. These participants had

actually filed complaints with DFI (or the office of Attorney General) regarding their

recent mortgage transactions and these sessions were formed to allow a more in-depth

understanding of these individuals‘ mortgage experiences, as well as to support the

survey findings.

The results showed statistically significant differences between two population pools and,

in general, the results were less positive for respondents in the victim pool compared to

those in the general pool. In particular, the victim pool had less understanding of specific

financial terms that were thought to have a critical impact on decisions regarding loans.

Respondents in the victim pool were less likely to invest in stocks, have long term

savings and financial plans, spread their investments, or invest in retirement plans. These

respondents also showed higher tendencies towards risky behaviour.

This study also recognized financial illiteracy as a concern amongst Washington State

residents and the main purpose of the study was to provide DFI with the information

needed for them to develop an effective financial literacy program to educate, inform and

217 Moore, D. (2003). Survey of financial literacy in Washington State: Knowledge, behaviour, Attitudes,

and Experiences. Technical Report # 03-39. Social and Economic Sciences Research Center, Washington

State Department of Financial Institutions, Olympia, WA . Puulman: Washington State University.

66

assist consumers in making financial decisions. Although the results indicated that

consumers would benefit from such a program, especially those in the victim pool, the

major challenge identified was to motivate participation.

2.8.2.4 Hilgert, Hogarth and Beverly (2003218)

Hilgert, Hogarth and Beverly (2003) used results from the University of Michigan‘s

monthly Survey of Consumers (conducted in November and December 2001) to explore

the connection between financial knowledge and behaviours. A financial practice index

was calculated for each of the four financial management activities: cash-flow

management, credit management, saving and retirement. Each index comprised three

categories: low, medium and high, and the survey respondents were placed into these

categories based on their participation in each activity.

In addition, a financial knowledge score was calculated across five sections: credit

management, saving, investment, mortgage, and other. The average financial knowledge

score was examined by the financial practice index and index level. Differences were

revealed between financial practice index and financial knowledge scores, indicating that

there is a relationship between behaviour (as measured by the index) and knowledge (as

measured by score). In general, medium to high index levels were associated with higher

scores under most sections of knowledge. Research confirmed a correlation between

financial knowledge and behaviour, although the direction of the causality is unclear. It is

also concluded that those who score higher on financial literacy tests are more likely to

follow recommended financial practices. Compared with those who have less financial

knowledge, those with more financial knowledge are also more likely to follow

recommended financial practices and engage in recommended financial behaviours.

2.8.2.5 Chen and Volpe (2005219)


between knowledge and behaviour. Federal Reserve Bulletin, 89 (July): 309-322.Washinton, D.C.

67

Chen and Volpe (2005) conducted a survey of 212 company human resource and benefits

administrators to find out the financial literacy of the U.S. workers. The survey

instrument was consisted of 68 questions focusing on importance of various personal

financial topics, the level of knowledge possessed by employees, whether inadequate

personal finance knowledge leads to a decline in productivity, the use of a financial

literacy test to screen new hires and the most effective approach to improve employee‘s

financial literacy in the workplace.

The results of the survey showed that participants ranked all of the surveyed personal

finance topics as important and that they believed that employees do not have adequate

knowledge about these topics. Retirement planning was ranked as being the most

important topic, followed by personal finance basics, insurance, company benefit plans,

taxes, investments and estate planning. Respondents identified that the least

knowledgeable areas among employees are financial planning basics and retirement

planning.

More than 55 % of respondents who answered a question about whether inadequate

personal finance knowledge leads to a decline in productivity believed that this is the

case, although a few respondents recommended using a financial literacy test to screen

new hires. Results of the survey also showed that respondents believed that outsourcing

to outside financial planners is the most effective approach to educating employees on

personal finance.

2.8.2.6 National Council on Economic Education (2007220)

219 Chen, H. &Volpe, R. P., (2005). Financial literacy, education, and services in the Workplace. B>Quest

(Business Quest). A Journal of Applied Topics in Business and Economics. Available at

http://www.westga.edu/~bquest/2005/workplace.pdf. retrieved on March 22, 2010. 220 National Council on Economic Education, (2007). Economic, Personal Finance & Entrepreneurhip

Education in Our Nation's Schools in 2007. New York: National Council on Economic Education.

http://www.westga.edu/~bquest/2005/workplace.pdf.%20retrieved%20on%20March%2022

68

The National Council on Economic Education attempted to investigate personal financial

education in schools across all states by running a biennial survey, the first survey was

conducted in 1998 (NCEE, 2005221) and the second survey in 2004. Results of the later

survey revealed that only 34 states had standards for personal finance and 20 of these

required that these standards be implemented. In addition, only six states required that

students complete a course that covers personal finance before graduating from high

school and only eight states actually tested students‘ personal financial knowledge. From

the results of this survey, it was concluded that the vast majority of young people in the

U.S. were not being taught about personal finance in school.

2.8.2.7 Lusardi and Mitchell (2006222)

Lusardi and Mitchell (2006) developed a module on retirement planning and financial

literacy as part of Health and Retirement Study conducted in 2004 in The United States.

The module aimed to explore the hypothesis that poor planning may be a primary result

of financial illiteracy. In order to do this, the module measured how workers make their

saving decisions, how they collect information for making these decisions, and whether

they possess required amount of financial literacy needed to make these decisions.

A total of 1,269 adults aged over 50 years responded to the module and results showed

that there is a strong relationship between financial knowledge and planning; in that those

with financial knowledge were more likely to plan and to succeed in their planning. They

also found that overall, financial literacy is poor among older Americans and certain

groups are particularly at risk. In addition to this, they also found that the least literate are

also the least likely to plan and save for retirement.

2.8.2.8 Lusardi and Mitchell (2009223)

221 National Council on Economic Research. (2005). What American teens and adults know about Economics. Washington, D. C. 222 Lusardi, A. &Mitchell, O.S. (2006). Financial literacy and planning: Implications for Retirement

Wellbeing. Michigan Retirement Centre. Working Paper 2005-108, Michigan United Sates, October 2006. 223 Lusardi, M.& Mitchell, O. (2009). How ordinary consumers make complex Economic decisions:

Financial literacy and retirement readiness. NBER working paper No. 15350.

69

Based upon the findings of previous research , the least literate are also likely to plan and

save for retirement (Lusardi and Mitchell, 2006; 2007a224; 2008225), Lusardi and Mitchell

developed a study to report on several self-assessed and objective measures of financial

literacy newly added to the American Life Panel (ALP), and identify the links between

financial literacy and retirement planning by exploiting information about respondents‘

financial knowledge acquired in school – before entering the labor market and certainly

before starting to plan for retirement. The Rand American Life Panel (ALP) was an

internet based survey of respondents age 18+ recruited by the University of Michigan‘s

Survey Research Center. They used two sets of questions to test economic knowledge of

population.

The first set followed HRS approach which captured people‘s capacity to handle basic

financial literacy concepts, which intended to measure simple concepts crucial for

everyday financial transactions and decision making. This set included the questions

based on numeracy, compound interest, inflation, time value of money and inflation/

money illusion. From 989 observations taken from ALP, it was found that 87.1%

respondents can do simple calculations regarding interest rates and they also understand

the effects of inflation. Yet al.most three quarters of respondents (69.0%) cannot give

correct answer about compound interest. Similarly, a sizable fraction of respondents

(78.4%) suffer from money illusion. Moreover, fewer than half (47%) of the respondents

can correctly answer all the five questions. Moving towards socioeconomic

characteristics, respondents aged 50+ were more consistently better informed, although

the age differences were not often statistically significant. Those who had not attended

the college were more likely to respond incorrectly. It was also found that women

exhibited much lower levels of financial literacy than men, where sex differences were

statistically significant for all except money illusion question. These findings were

similar to those in the older sample of Health and Retirement Survey (HRS).

224 Lusardi, Annamaria & Olivia S. Mitchell (2007a). Baby Boomer Retirement Security: The Role of

Planning, Financial Literacy, and Housing Wealth. Journal of Monetary Economics, 54, 205–224. 225

Lusardi, A. & Tufano, P. (2008). Debt literacy, financial experiences, and over-indebtness. Dartmouth

Working Paper.

70

The second set was used to capture sophisticated financial literacy, and measured

responses to more advanced application based financial knowledge questions. Both the

sets also included self assessment questions, which are intended to reflect people‘s

confidence about understanding of economics. With the same number of observations, it

was found that most respondents responded to most of the questions correctly. The

respondents were found to be knowledgeable about the functioning of stock markets and

diversification. They were also found to be more knowledgeable about the fluctuations in

assets than about patterns of asset returns. But the questions linked to bond prices and

interest rates proved very difficult. Only 16% respondents could answer the questions

correctly confirming that sophisticated financial literacy was not widespread. Under the

socio economic characteristics, it was found that younger respondents were less well

informed. In addition, it was found that better educated respondents were more

knowledgeable than less educated counterparts. Sex differences were also marked in that

women knew substantially less than men with regards to the stock market, risk, and bond

returns versus stocks, risk diversification, and basic asset pricing.

They used multivariate analysis to link retirement planning with financial literacy,

holding other socioeconomic factors constant. Under the ordinary linear multivariate

regression it was found that financial knowledge is influential in retirement planning. But

sophisticated financial knowledge is the most important factor, while basic literacy is not

that statistically significant. The overall findings of this study suggested that the impact

of financial literacy index in the retirement planning is positive, statistically significant

and it strongly influences retirement planning.

2.8.3 Australian Studies

2.8.3.1 Beal and Delpachitra (2003226)

226 Beal, D.J. & Delpachtra, S.B. (2003). Financial literacy among Australian university students, Economic

Papers, 22 (1), 65-78.

71

The first Australian financial literacy survey was conducted in 2002 by Beal and

Delpachitra (2003) on a sample of students from the University of Southern Queensland.

The survey was targeted a first year students across five disciplines: Arts, Business,

Education Engineering and Surveying and Sciences. In addition, students studying

psychology as a major and some post-graduate psychology students were targeted. It was

found that many psychological problems in the community are connected with financial

difficulties and so practicing psychologists should have an understanding of personal

financial issues, hence the interest in gaining an understanding of the levels of financial

literacy among psychology students.

Complete primary data was collected from 789 students, through which the following

five main skills were tested by asking technical multiple choice questions: basic concept,

markets and instruments of financial markets, planning, analysis and decision making,

and insurance.

The methodology used to analyze the survey responses was very similar to that of Chen

and Volpe (1998227). Results for the first main area of skill, ‗basic concepts‘, showed that

questions best answered was about how saving is achieved, where students correctly

answered 97.1 percent of cases. The question that was worst answered in this area

queried about the balance in the bank account where an initial $ 100 had been deposited

for one year at 12 percent simple interest versus 1 percent per month compound interest,

in which only 52.9 percent of respondents answered correctly. Another poorly answered

question in this area was reason for diversifying an investment portfolio, in which only

58.5 percent of students answered correctly. These results indicated that simple concepts

in finance, such as the effect of compounding interest and the relationship between risk

and return, are not well understood by university students.

Results for the second main area of skill, ‗markets and instruments of the financial

markets‘, showed that the question best answered was one that queried about the nature

227

Chen, H. &Volpe, R. P., (1998). An analysis of personal financial literacy among college students.

Financial Services Review , 7 (2), 107-128.

72

of the liability undertaken when guaranteeing a friend‘s loan. This question was correctly

answered by 87.5% of respondents. Majority of the remaining questions for this main

area of skill were poorly answered. Only 44.1 percent of students understood the role of

the cash rate in the economy and only 36.7 percent of students were able to correctly

identify which Australian asset class has given the best returns over the last two decades.

These results strongly confirmed that many students are not aware of common financial

information.

Results for the third main area of skill, ‗financial planning‘, showed that the best

answered questions queried about the advantages of keeping a daily track of expenditure

and about the awareness of bank statements allowing them to keep watch on interest rates

and bank charges. The worst answered question, to which only 27.9 percent of students

answered correctly, required respondents to indicate the correct method of subtracting

outstanding cheques from the apparent balance on a bank statement to achieve the actual

balance. These results indicate that the majority of participating students have a poor

understanding about the method of effecting bank reconciliation.

Results for the fourth main area of skill examined, ‗analysis and decision making‘,

showed that solving financial problems together with the knowledge of insurance matters

were the areas which students generally answered least well. The best answered question

where 64.5 percent of respondents answered correctly, involved mortgage-buster or

saving offset accounts. The best method to rectify a persistent credit card debt was able to

be identified correctly by 58 percent of respondents and only 43.1 percent of respondents

were able to correctly solve a simple present value problem. The worst two answered

questions involved an asset-rich, cash-poor person getting funds quickly for an urgent

medical procedure (36.3 percent correctly answered) and a calculation of the best deal on

a motor vehicle in which only 33 percent of respondents answered correctly.

The final main skill areas that were examined paying attention on insurance and results

showed that 77 percent of respondents were correctly able to identify the determinants of

vehicle insurance premiums. Approximately 57 percent understood the nature of

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insurance excesses, but only 42 percent were able to identify the risks covered by

compulsory third party vehicle insurance. The worst answered questions involved flood

not normally being covered by householders‘ policies (31.6 percent answered correctly)

and the nature of term life insurance, in which only 21.5 percent of respondents were able

to answer correctly. These results indicated that while students appear to have a

reasonable knowledge about vehicle insurance, many are lacking knowledge about other

types of insurance, such as household and life insurance.

Analysis of the full model showed that five independent variables, major, sex,

occupation, experience and risk preference impact significantly on the dependent

variable. The significant demographic variables are sex, work experience, income and

risk preference. Students with higher financial literacy scores were more likely to be

male, have greater work experience, have a higher income and have a lower aggregate

risk preference. An analysis of the first of the five separate models showed that students

with higher general financial knowledge and skills were more likely to be studying

business, be male, working in more highly skilled occupation and have more work

experience. Overall, it was concluded that university students in Australia were not

skilled nor knowledgeable in financial matters and that this will tend to impact negatively

on their future lives through incompetent financial management.

2.8.3.2 ANZ Bank Study (2003228)

In 2003, Roy Morgan Research conducted Australia‘s first national survey on financial

literacy on behalf of the ANZ bank (RMR, 2003). There were two components of the

study: a telephonic survey of 3,548 adults and an in-depth survey of 202 people which

included a self component and an in-depth interview of around one to one and a half

hours each. The telephone survey consisted of 145 finance and 25 demographic

questions. The finance questions were split into four categories: mathematical and

standard literacy, financial understanding, financial competence and financial

228 Roy Morgan Research . (2003). ANZ Survey of Adult Financial Literacy in Australia. ANZ Banking

Group. Melbourne: Roy Morgan Research.1-77.

74

responsibility. The objective of this study was to test the knowledge of respondents

against an individual‘s needs and circumstances and hence not all the respondents were

asked all the questions. As a result, a bias in the results has been generated that

respondents were asked only questions about the financial products and services that they

currently use, then it could be expected that their knowledge of such products and/or

services would be higher than the respondents who does not use that particular product or

service. Use of self-rating questions in the survey also introduced a bias in the findings of

study.

Despite these limitations, the ANZ survey attempted to measure knowledge and

understanding, behaviour, attitude, perceptions and awareness as they related to the four

categories mentioned above, rather than simply measuring skills. In addition to this, the

chosen sample was highly representative of Australian population, with confidence

interval of less than + 2 at the 95 % confidence level. In the analysis, ten levels of

financial literacy were used which were combined to form financial literacy quintiles,

where quintile one was the lowest level of financial literacy and quintile five was the

highest. Correlations, averages and percentages were also used to summarize results. The

survey findings showed that Australians overall are a financially literate society, but that

certain groups have particular challenges that need to be addressed. Those groups were

identified as those having lower level of education, those not working or in unskilled

work, those with lower incomes (household income under $ 20,000), those with lower

saving levels (under $5,000), single people and people at both extremes of the age profile

(18-24 years old and those above 70 years). In contrast, respondents in the highest

financial quintile were males, people with tertiary degrees, professionals and business

owners, couples with no children and people aged between 45 and 59 years. Thus, despite

respondents only being tested on the issues relevant to their current circumstances, a

strong correlation was found between financial literacy levels and socio economic status.

2.8.3.3 Commonwealth Bank Study (2004229)

229 Commonwealth Bank Foundation. (2004). Improving Financial Literacy in Australia: Benefits for teh

individual and the Nation. Sydeny: Commonwealth Bank Foundation.

75

The CBF‘s survey on financial literacy was the first study that investigated the strength of

association between financial literacy and outcomes for both individuals and the

Australian economy. This was achieved in three phases. The first phase was a national

telephonic survey of 5,000 Australians aged between 16 to 65 years; the second phase

investigated the microeconomic effects of improving financial literacy, and the third

phase investigated the macroeconomic effects of improving financial literacy.

The national telephonic survey consisted of 20 multiple choice questions. The survey was

designed to test each respondent‘s ability to make financial decisions, rather than testing

knowledge of financial information. The survey also collected demographic information

such as personal finances, whether the individual had ever owned a business, personal

and health history, and sources of financial knowledge.

The results of the survey showed that those who were unemployed had poorer financial

literacy skills. Also among this group were younger people (aged 16-20 years), males,

students, people with lower levels of education, people with lower personal income

(under $ 10, 000), people with lower annual household income (under $ 50,000) and

people who had never worked in paid employment. Participants with these demographic

characteristics made up 10 percent of the respondents with the lowest financial literacy

scores. Results of the survey also showed that people in older age groups displayed lower

financial literacy, suggesting that financial literacy was not merely a function of age or

life experience.

Results also indicated that the higher an individual‘s financial literacy, the lower the

probability that they were unemployed. In addition, lower financial literacy was found to

have an impact on an individual‘s health. The survey also revealed that 85 percent of

respondents primarily learn about managing their finances through experience or ‗trial

and error‘, and a significant proportion of respondents (36 %) specified financial

institutions as a source of their financial knowledge.

76

The second phase of the study revealed that improvements in financial literacy can result

in lifestyle gains for individuals of all ages, across the whole community (p.4). For those

respondents who had the lowest levels of financial literacy, the expected probability of

unemployment was 14.3 percent, compared to 1.7 percent for those who had the highest

levels of financial literacy. Further, there was evidence that a modest improvement for

the financial literacy of the 10 percent of respondents who had the lowest financial

literacy scores, would have resulted in these people having an average increase in annual

income of $3,204.

The third phase of the study revealed that an improvement in financial literacy has the

potential to create more than 16,000 new jobs boosting Australia‘s economy by $ 6

billion per annum (CBF, 2004, p. 3). Other anticipated macroeconomic effects of

improving financial literacy includes the strengthening of national savings, a boost to

both public and private consumption, and the creation of more successful small

businesses.

2.8.4 The Singapore Study

2.8.4.1 MoneySENSE (2005230)

The MoneySENSE Financial Education Steering Committee 231 (FESC) (2005)

commissioned a national survey of 2,023 Singapore citizens and Permanent Residents.

The basic objective of the study was to measure the current levels of financial literacy

among different segments of the Singapore population with reference to their financial

knowledge and understanding of common financial products and services and the actions

taken by Singaporeans in dealing with financial matters. The questionnaire was divided

230 MoneySENSE (2005). Quantitative Research on financial literacy levels in Singapore. THe

MoneySENSE Financial Education Steering Committee. Singapore: Media Research Consultants Pvt. Ltd. 231 TheMoneySENSE Financial Education Steering Committee was formed in February 2003 to provide

strategic direction and oversight of financial education programmes in Singapore. It comprises

representatives from the Monetary Authority of Singapore, Ministry of Community Development, Youth

and Sports, Ministry of Education, Ministry of Manpower, Central Provident Fund Board, and People‘s

Association.

77

into three tiers namely, basic money management, financial planning and investment

know-how. The findings of the study showed that the mean financial literacy score

including knowledge and action for tier I was 74 and for tier II, it was 62 from a total of

2023 respondents. Mean financial literacy score for tier III was 67 out of 662 who had

invested.

2.8.5 OECD Study (2005232)

With an objective to identify financial literacy skills and knowledge possessed by the

consumers and to establish the baseline measurement of financial literacy for policy

makers and financial institutions OECD has conducted financial literacy surveys in

selected five countries (Australia, Japan, Korea, The United States, and the United

Kingdom). These surveys exhibited two different approaches for measuring financial

literacy. One approach was to give respondents an objective test that measures their

knowledge and understanding of financial terms and their ability to apply financial

concepts to particular situations. Surveys of this type were undertaken in the United

States and Korea and were targeted at high school students. The other approach was to

ask respondents for a self assessment, or for their self perceptions, about their financial

understanding and knowledge, as well as for their attitudes towards financial instruments,

decisions, information and its receipt. This was the approach used by the surveys

undertaken in the United Kingdom, Japan, and Australia, although the Australian survey

has also included some of the objective measurement of financial literacy.

Although, the surveys differed in target audience, approach for measuring financial

literacy and survey methodology, there are a number of similarities in the results. Among

which,

1. All the surveys found low level of financial understanding among respondents.

232

Organization for Economic Co-operation and Development (2005). Improving Financial Literacy:

Analysis of Issues and Policies. Paris, France : OECD Publications.

78

In Australia, 67 per cent of respondents indicated that they understood the concept of

compound interest, yet when they were asked to solve a problem using the concept,

only 28 per cent had a good level of understanding.

A British survey found that consumers do not actively seek out financial

information. The information they do receive is acquired by chance, for example, by

picking up a pamphlet at a bank or having a chance talk with a bank employee.

A Canadian survey found that respondents considered choosing the right investments

to be more stressful than going to the dentist.

A survey of Korean and American high-school students showed that they had failing

scores - that is, they answered fewer than 60 per cent of the questions correctly - on

tests designed to measure their ability to choose and manage a credit card, their

knowledge about saving and investing for retirement, and their awareness of risk and

the importance of insuring against it.

A survey in The U.S. found that four out of ten American workers are not saving for

retirement.

The Japanese Consumer Survey on Finance found that 71 percent of adult

respondents had no knowledge about investment in equity and bonds, 57 percent had

no knowledge of financial products in general, and 29 percent had no knowledge

about insurance, pension and tax.

2. The surveys that included the questions about respondents‘ social characteristics found

that financial understanding is correlated with education and income level.

In Australia, the lowest level of financial literacy are associated with low levels of

education (year 10 or less), unemployment or low skilled work, low incomes

(household income under $ 20,000), low levels of savings (under $ 5,000), being

single, and being at either end of the age profile (18 to 24 years old and those

aged 70 years or older).

In the United Kingdom, individuals in the lower social grades and the lowest

income band, as well as young people aged 18 to 24, are likely to be the least

receptive consumers and also uninterested, unconfident and least active. By

79

contrast, the higher social grades, those with higher income, young couples and

older respondents with no family are more likely to be sophisticated financial

consumers, knowing how to get the information they need and understanding the

advice they receive.

In the Korean and American surveys, scores broken down by demographic

characteristics indicate that students from families with less educated parents

and/or students who have low income and professional expectations score the

lowest.

3. The surveys found that respondents often feel they know more about financial matters

than is actually the case.

Respondents in United States, The United Kingdom, and Australia felt confident

in their knowledge of financial issues even though when given a test on basic

finance, it was clear that they had only limited understanding of these issues. It

was found that if consumers do not realize they need information, they will not be

in a position to seek it.

The survey in United Sates found that 65 percent of students said that they are

somewhat sure or very sure of their ability to manage their own finances.

However, the scores of these students were not much higher than those of their

less confident peers, which suggested that, the students are unable to judge

accurately how capable they are to manage their money.

When asked for their perceptions, most respondents to the Australian survey

stated that they are financially literate. However, when asked to apply their

financial knowledge to solve a particular problem, they demonstrated a lack of

financial understanding. Although 67 percent of respondents indicated that they

understand the concept of compound interest, only 28 percent correctly answered

a problem using this concept.

4. The surveys found that respondents often feel financial information is difficult to find

and understand.

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The Japanese Consumer Survey on personal finance found that respondents felt

frustrated about the difficulty in finding easy-to-understand information on

financial products. When asked about the financial information provided by

various organizations and companies, 39 percent of respondents said they had not

seen much information and 29 percent found the content of the information

difficult and hard to follow.

The British survey conducted in the United Kingdom found that consumers do not

actively seek out financial information. The information they do receive is

acquired by luck or chance or hazard, for example, picking up a pamphlet at a

bank or having a chance to talk with a bank employee. This survey also found that

consumers‘ perceived complexity of financial products is one reason given for not

going ahead for purchase.

2.9 Domestic Scenario

2.9.1 India Protection Survey - How India Earns, Spends and Saves (2007233)

National Council for Applied Economic Research and Max New York Life Insurance

Company Limited did a study titled ―India Protection Survey - How India earns, spends

and saves‖ and developed a data on attitudes and practices that have a bearing on the

financial security of Indian households. The survey collected the data from sample size of

over 63,000 households spread across the length and breadth of the country. The survey

found that out of 86 percent of Indian household that save, 36 percent keep their saving at

home as cash. The results also say that India saves primarily for emergencies (83

percent), wedding and social events (63 percent), children‘s education (81 percent) and

inheritance, old age (47 percent). The results also show that less than 3 percent buy bonds

233 Max New York Life Insurance Company Ltd. & National Council for Applied Economic Research

.(2007). How India Earns, Spends and Saves: India Financial Protection Survey. Delhi: Max New York

Life Insurance Company Ltd. and National Council for Applied Economic Research. Research Report.

81

and other financial instruments. The survey also found little correlation between saving

and long term gain. The survey concluded that the lack of long term financial planning

and poor levels of financial literacy comprise of the core of India‘s financial insecurity.

2.9.2 Financial Literacy and Domestic Regulatory Authorities

The Reserve Bank of India launched an initiative in 2007 to establish Financial Literacy

and Credit Counseling Centers throughout the country which would offer free financial

education and counseling to urban and rural populations. The broad objective of the

FLCCCs is to make the people in urban and rural areas educated and aware about various

financial products and services available from the formal financial sector and providing

them free financial literacy/education and credit counseling.

The Reserve Bank has undertaken a project titled 'Project Financial Literacy'. The

objective of the project is to disseminate information regarding the central bank and

general banking concepts to various target groups, such as, school and college going

children, women, rural and urban poor, defense personnel and senior citizens. The

information is disseminated to the target audience with the help of among others, banks,

local governments, NGOs, schools, and colleges through presentations, pamphlets,

brochures, films, as also through the website. It also disseminates the financial

information through its web site in English, Hindi and 12 other Indian regional languages

to provide ease for access to the public.

Securities and Exchange Board of India (SEBI) promotes financial literacy through

financial education with the help of investors associations and through the resource

persons empanelled by it. The first panel of resource persons was empanelled in June,

2010; under this initiative, six target groups are identified to promote financial literacy.

These are: school children, college going students, middle income groups, executives,

home makers and retirees. The financial literacy information is disseminated through

presentations, pamphlets, brochures etc. SEBI has also started to spread financial

http://www.rbi.org.in/scripts/PublicationDraftReports.aspx?ID=526

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education to school children through ‗pocket money program‘ with National Institute of

Securities Market.

2.10 Theoretical Framework for Financial Behaviour

Consumer Economists have studied financial behaviour for the last three decades.

Fitzsimmons, Hira, Bauer and Hafstrom (1993234) did a study on financial behaviour from

1970s to early 1990s. The trend has continued through the years and recently, there have

been more studies on financial behaviour (Hilgert, Hogarth & Beverly, 2003235; Hogarth,

Hilgert, and Schuchardt, 2002236; O‘Neill & Xiao, 2003237; Xiao, 2006238).

Xiao (2008239) said that ―financial behaviour can be defined as any human behaviour that

is relevant to money management. The common financial behaviour includes cash, credit,

saving and investment behaviours‖ (p. 70).

As discovered by economic psychologists, there are certain human psychological

behaviour patterns that impact individuals‘ financial behaviours. They have identified the

contextual factors that influence decision making. Personal finance is an interdisciplinary

subject and derives its context from subjects such as family studies, economics,

psychology, and sociology.

Theory is a general framework of ideas. A pattern emerges, after collection of specific

types of data, and a theory is developed to provide explanation for this pattern. This topic

describes theoretical frameworks to explain individual financial behaviour.

234 Fitzsimmons, V. S., Hira, T. K., Bauer, J. W., & Hafstrom, J. L. (1993). Financial management:

Development of scales. Journal of Family and Economic Issues, 14, 257-273. 235 Hilgert, M.A., Hogarth, J.M. & Beverly, S.G. (2003) Household financial management: The connection

between knowledge and behaviour. Federal Reserve Bulletin, 89 (July): 309-322.Washinton, D.C. 236 Hogarth, J. M., Hilgert, M. A., & Schuchardt, J. (2002). Money managers: The good, the bad, and the

lost. Proceedings of the Association of Financial Counseling and Planning Education, 12-23. 237 O'Neill, B., & Xiao, J. (2003). Financial fitness quiz: A tool for analyzing financial behaviour.

Consumer Interests Annual, 49, American Council on Consumer Interests. 238 Xiao, J. J. (2006). Applying behaviour theories to financial behaviour. In J. J. Xiao (Ed.),

Handbook of consumer finance research (pp. 69–81). New York: Springer. 239 Xiao, J. J. (2008). Handbook of Consumer Finance Research. p. 70

83

2.10.1 Goal Setting Theory

Edwin Locke (1960s240) has given the Goal-setting theory of motivation. The theory

states that in any measure of task performance, goal setting is the essential element. In

other words, according to this theory, goal setting should be essentially linked to task

performance. It explains that not only the specific goals but also the goals which

challenge individuals to achieve something addition to the specific goals along with

appropriate feedback contribute to higher and better task performance. Work on the

theory of goal-setting suggests that it's an effective tool for making progress by ensuring

that participants in a group with a common goal are clearly aware of what is expected

from them if an objective is to be achieved. At an individual level, setting of goals is a

process that allows people to specify the task to be performed for achieving their own

objectives and/or goals. The goal setting theory is the most valid and useful motivation

theory not only in industrial and organizational psychology, human resource

management, and organizational behaviour but also in the field of financial behaviour. In

the context of personal finance, financial planning and investment decision, the goals

must be S.M.A.R.T. (Specific, Measurable, Achievable, Realistic, Time-Bound (SEBI,

2010241).

2.10.2 Human Ecological Model

The human ecological model was proposed by Bronfrenbrenner (1979242). It describes

individuals as dynamic factors that often influence and are influenced by interaction with

and within larger and interdependent systems. The four basic systems that make up the

ecological environment are the microsystem, the mesosystem, the exosystem, and the

macrosystem. The microsystem includes immediate family, friends, classmates or

employees, and members of one's faith community. The second level, the mesosystem,

240

Lucke. E. A. (1968). Toward a theory of task motivation and incentives. Organizational Behaviour and

Human Performance, 3, 157-189 241

Securities and Exchange Board of India. (2010, July). Financial Education for School Children, p. 5. 242 Bronfenbrenner, U. (1979). The Ecology of Human Development. Cambridge, MA: Harvard University

Press.

84

recognizes that parts of the micro system interact with each other and with the other

systems. The third level, the exosystem, includes groups, organizations, or entities that

influence the micro system. The fourth level, the macro system, surrounds and affects all

other systems. It includes cultural values, personal and social conditions, political

ideologies, and market and economic performance. Studies on financial behavior suggest

that the theory of human ecological model does have its impact on the decisions made by

families and the reciprocal interactions of families and environments.

2.10.3 Family Management Systems

Deacon and Firebaugh (1988)243 used the human ecological model and systems theory as

a base to provide a context for understanding the goal-directed behaviour of families. The

important components of systems theory are inputs, throughputs, and outputs. In the

family systems, the demands and resources enter the managerial subsystem as inputs. The

activities, through which families clarify their demands and assess their resources to

attain their goals, are known as throughputs. Then, a particular sequence of actions to

achieve the goal is developed, and a plan is implemented, known as an output. Feedback

provides information to various parts of the system for their use. This managerial process

outlined by Deacon and Firebaugh is similar to any investment decision that underlie a

financial planning process: setting goals, gathering data, analyzing information,

developing a plan, implementing the plan, and monitoring progress toward the goal.

2.10.4 Discounted Utility Model

The discounted utility framework was initially developed to incorporate inter-temporal

considerations into the formal models of decision making employed by economists and

other social scientists. Introduced by economist Paul Samuelson in 1938, the model states

that costs and benefits occurring at different times can be made comparable by

243 Deacon, R. E., & Firebaugh, F. M. (1988). Family resource management: Principles and applications

(2nd ed.). Boston: Allyn and Bacon.

85

discounting future utility244 by some constant factor. Economists assume that when a

person is faced with a choice from amongst a number of possible options, the person will

choose the one that yields the highest utility to him/her. However, people are constrained

by the amount of their income. The utility function assessed both in terms of current and

future consumption. According to this discounted utility model, what one gets in the

future is less valued now than it will be later.

2.10.5 Life Cycle Hypothesis of Savings

The life cycle hypothesis of savings developed by Ando and Modigliani (1963 245 )

assumes that a person consumes a constant percentage of their income over the life cycle

and that they are born without an inheritance and die without leaving a bequest.

According to this theory, many young investors would prefer to borrow to finance

consumption while they acquire education and skills. At middle stage of their lives, they

are expected to repay early debts and save for later life. In retirement, they are expected

to spend down their accumulated assets. However, many retired individuals continue to

save and also plan to transfer their remaining wealth to the next generation or to

philanthropic causes or organizations.

244 The utility of an option is a numerical value that refers to the option‘s consistency with the decision maker‘s preferences. Options that have higher utility are preferred to options with lower utility. The actual

numbers representing utility values are arbitrary; what matters are the relative utilities of the various

options. 245 Ando, A., & Modigliani, F. (1963). The life cycle hypothesis of saving: Aggregate implications and

tests. American Economic Review, 53, 55-84.

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Fig. 2.1 – An individual‟s financial life cycle and corresponding objectives

Source: Life cycle of financial planning by Gail M. Gordon, University of Wyoming Cooperative

Extension Service, 2001

The stage of life in which an investor finds himself, also plays an important role in

selecting the components of a particular investment portfolio and demands a strategic

focus for disciplined financial planning. These demographic factors play an important

role while predicting the expected financial obligation such as child‘s education, marriage

and provision for retirement.

In the context of investment decision as a part of financial planning, each stage in the

human life cycle, has a unique financial objective which needs to be fulfilled, which in

turn plays an important role in credit, saving and investment decisions.

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Table 2.1 Stage of Life Cycle, corresponding Objective- Needs and Requisite

Financial Behaviour

Objective Need Proposed Financial

Behaviour

Stage 1- To protect

yourself and your

family

Protection against risks of

unexpected circumstances and the

risk related to life, disability,

health etc.

Setting up of emergency

fund or to purchase

adequate amount of

insurance

Stage 2- To provide

for financial security

for yourself and your

family

To provide financial security to

extended family members,

fulfilling the needs for education,

social events, or fulfilling other

needs

Providing adequate

financial security without

placing undue stress on

your resources which may

result in financial crises,

emphasis on proper credit

& debt management

Stage 3- To enjoy a

comfortable standard

of living

To accumulate the wealth for

secured retirement

Budgeting financial

security for retirement,

State 4- To be

financially

independent,

Being financially independent

and have comfortable retirement,

with the same standard of living

Enjoying the return made

during the stage 1 and

stage 2

Stage 5- To

distribute the wealth

To distribute the wealth to the

beneficiaries or next generation

Following up the strategy

of estate planning

Source: Jariwala, H. (2010). Strategic approach to investment: A new paradigm in financial planning. In I.

E. Centre (Ed.), The Role of Financial Innovation:Corporate Sustenance and Growth. Mumbai: Excel India

Publishers.

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2.10.6 Behavioural Life Cycle Hypothesis

Thaler and Shefrin (1981 246) developed a theory of self control which suggests that

individuals have personality traits to be either a planner who is focused on deriving utility

both in the present and in the future or a doer who is focused on the present. Later, they

proposed the behavioural life cycle hypothesis (Shefrin & Thaler, 1988247) suggesting that

individuals practice mental accounting, meaning that they have different propensities to

save in different categories of accounts. For example, they may think differently about

funds in a retirement account than those in a cash reserve for emergencies. Thus, the

main tenet of this theory suggests that individuals might be long- or short-term planners

and that they plan to use money in different accounts for different purposes.

2.10.7 Maslow‟s Need Hierarchy Theory and understanding the Financial Needs

In the context of financial behaviour, the financial need hierarchy is similar to Maslow‘s

need hierarchy theory (1943248), which defines that the lower, basic needs pertaining to

human survival must be met before the higher needs can be addressed, which are not

directly related to the survival but relate to the life enhancement and quality of life.

246 Thaler, R. H., & Shefrin, H. M. (1981). An economic theory of self-control. Journal of Political Economy, 89 (2), 392-406. 247 Shefrin, H. M., & Thalen, R. H. (1988). The behavioural life-cycle hypothesis. Economic Inquiry, 26,

609-643. 248 Maslow, A. (1943). A theory of human motivation. Psychological Review, 50, 370-396. Retrieved on

June 25, 2010, from http://psychclassics.yorku.ca/Maslow/motivation.html.

http://psychclassics.yorku.ca/Maslow/motivation.htm

89

Fig. 2.2 Financial Need Hierarchy

The explanation of these financial needs hierarchy is given below.

Survival money: The money that an individual spends simply to survive.

What-if money: The money required to protect the life.

Freedom money: The money needed to do the things that bring joy and

fulfillment to the life.

Gift money: This is the replacement for ―love‖.

Dream money: This is the elusive ―self-actualization‖ level where an individual

finds true happiness and meaning.

The decisions regarding savings, ownership of investments and choice of credit

instruments also depend upon individual‘s financial needs (or objectives) and abilities

(resources) to acquire these financial assets and liabilities (Katona, 1960249). The financial

need priorities which a household has and the resource availability at each stage of a

household‘s life cycle determine the sequence in which financial services and/or

instruments are acquired by the household.

2.10.8 Theory of Reasoned Action and Theory of Planned Behaviour

249 Katona, G., (1960). The powerful consumer. New York: Mc-Graw Hill.

Survival

MoneyWhat-if Money

Freedom Money

Gift Money

Dream Money

90

Ajzen and Fishbein (1980250

) formulated the theory of reasoned action (TRA). Theory of

Reasoned Action suggests that a person's behaviour is determined by his/her intention to

perform a specific behaviour in a particular situation and that this intention is, in turn,

depends on his/her attitude toward the behaviour and his/her subjective norm. The best

predictor of behaviour is intention. Intention is the cognitive representation of a person's

readiness to perform a given behaviour, and behaviour is immediately preceded by

intension. Intention is determined by three things: attitude towards the specific behaviour,

subjective norms and perceived behavioural control. The theory of planned behaviour

holds that only specific attitudes towards the behaviour in question can be expected to

predict that behaviour. In addition to attitudes toward the behaviour, measuring people‘s

subjective norms is also important. Subjective norms are people‘s beliefs about how

people they care about will view the behaviour in question. To predict someone‘s

intentions, knowing these beliefs can be as important as knowing the person‘s attitudes.

Finally, perceived behavioural control influences intentions. Perceived behavioural

control is how people perceive their ability to perform a given behaviour. These

predictors lead to intention. As a general rule, the more favorable the attitude and the

subjective norm, the greater the perceived control, the stronger would be the person‘s

intention to perform the behaviour in question.

2.10.9 Transtheoretical Model of Behaviour Change

Prochaska (1979 251 ) developed the transtheoretical model (TM) from a comparative

analysis of leading theories of psychotherapy and behaviour change. This model

underpins the different levels of readiness to change a problem behaviour or develop a

desirable behaviour. Prochaska and DiClemente (1983252) developed six steps under this

model, which are (a) precontemplation, (b) contemplation, (c) preparation, (d) action, (e)

250 Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting behaviour. Englewood Cliffs,

NJ: Prentice Hall. 251 Prochaska (1979) developed the transtheoretical model (TM) from a comparative analysis of leading

theories of psychotherapy and behaviour change. 252 Prochaska, J. & DiClemente, C. (1983). Stages and processes of self-change of smoking: toward an

integrative model of change. Journal Consulting Clinical Psychology 51(3), 390–395 retrieved on May 21,

2009

http://www.uri.edu/research/cprc/Publications/PDFs/ByTitle/Stages%20and%20Processes%20of%20self%20change.pdf

http://www.uri.edu/research/cprc/Publications/PDFs/ByTitle/Stages%20and%20Processes%20of%20self%20change.pdf

91

maintenance, and (f) termination. The stages of change are precontemplation (no

intention to change behaviour), contemplation (aware of problem but not committed to

changing behaviour), preparation (intending to change within a month), action (changing

the problem behaviour by employing a variety of strategies), and maintenance (working

to prevent relapse). Movement to a higher level of readiness to change behaviour is

influenced by the processes of change. The TTM involves ten processes of change.

Change processes include activities and experiences that individuals engage in as they

attempt to modify their behaviour. Each process is a broad category encompassing

multiple techniques, methods, and interventions. Research has shown that successful self-

changers employ a variety of strategies to achieve their goal. One of the important

concepts which has been tested by this theory is understanding how individuals can be

motivated to increase savings and reduce debt.

2.10.10 Myers-Briggs Type Indicator

This theory was developed by Carl Jung (1923 253) and later widely researched and

applied by various researchers, for better understanding of human behaviour. It says that

―essence of the theory is that much apparently random variation in behaviour, which is

actually quite orderly and consistent. If people differ systematically in what they perceive

and in how they reach to conclusions, then it is only reasonable for them to differ

correspondingly in their reactions, interests, values, motivations, skills and interests‖

(Myers & McCaulley, 1985254, p 1).

The MBTI was developed to help people understand and appreciate themselves and

others. These psychological type concepts concentrate on personal acceptance and

healthy differences among people. Since 1942, instrument items have been written,

validated, and subjected to tests for validity and reliability. The current form uses 94

items to identify four pairs of preference alternatives. Although every individual is able to

use all eight preferences, Jung‘s theory suggests that individuals are predisposed to use

253 Jung, C.G. (1923). Psychological Types. New York: Harcourt Brace. 254 Myers, I.B. & McCaulley, M.H. (1985). Manual: A guide to the development and use of the Myers-

Briggs Type Indicator. Palo Alto, CA: Consulting Psychologists Press, Inc.

92

one preference more than the other and that, through use, the preference is strengthened.

Validation studies indicate a high correlation between an individual‘s self-awareness and

the corresponding report generated from the answers to questions in the MBTI

instrument. The real value of this theory is that many people find exceptional personal

insight when introduced to the MBTI concepts.

Till date, there is limited attention on linkages between psychological types and financial

decision-making. Studies of general decision-making attempt to build a bridge of

understanding that can be used to connect specific type of personalities to specific

financial decisions. Huitt (1992255) describes decision-making differences among people

based on their psychological preferences. For example, some people naturally make

decisions based on logic and critical thinking. They employ analysis, backwards

planning, categorizing and classifying, challenging assumptions, judging, systematic

reasoning, and task analysis. Others make their best decisions when they use

brainstorming, visualizing, relaxing, taking another‘s perspective, and values

clarification.

The MBTI instrument measures four pairs of preferences. These concepts suggest that

individuals exhibit strengths based on their personality preferences selected from four

scales (Myres, 1980256

).

Extroversion/Introversion: The extroversion/intro-version set of preferences defines how

people are energized. Some people get their energy from the external world – extroverts.

They seek relationships with other people and often interpret their own thoughts in terms

of what other people think of their thoughts. They prefer generating ideas with a group

and want affirmation from friends and associates about their ideas. Extroverts are ready

and willing to talk about what they need and want. They do not give too much

importance to written material. They may hear what they want to hear, not what the

255 Huitt, W.G. (1992). Problem solving and decision making: Consideration of individual differences using

the Myers-Briggs Type Indicator. Journal of Psychological Type, 24, 33-44. 256

Myers, I.B. (1980). Gifts differing. Palo Alto, CA: Consulting Psychologists Press, Inc.

93

others are recommending. They may change their portfolio if convinced to do so by

others.

Introverts get their energy internally. They need time to think about all aspects of a

particular decision before speaking and don‘t like competing in fast-flowing

conversations. Introverts are often secretive about personal information and do not share

personal information with people they do not know well. They want written materials and

they want time to read them. They tend to concentrate, focus and reflect on information.

They are more likely to have conservative asset portfolios.

Sensing/Intuitive: Sensing and intuitive preferences describe the process that people rely

on to gather information. Sensing people trust their senses as they gather information and

want to turn the theory they have learnt into practical applications. They often ask, ―will

it work?‖ Sensing people are comfortable focusing on the present, have concrete ideas,

and are at their best dealing with specifics. These type of people like to deal with facts.

They look for practical application of financial concepts. They want information

presented in a sequential manner, and they like examples.

On the other hand, an intuitive person often rearranges information received into a new

idea based on hunches and inspiration. Intuitives enjoy brainstorming future possibilities,

and are good at describing the big picture. This type of personalities like planning to

address future needs but they may not be as interested when it comes to evaluating and

selecting a specific course of action.

Thinking/Feeling Thinking and feeling preferences describe how people make decisions

in terms of their thinking or feelings. People who prefer thinking work in a logical and

scientific manner. They take any decision based on numbers and figures. They would

prefer to be correct and do not pay too much attention to what other people their decision.

Logical implications underpin their decisions. Thinkers prefer to be objective. This

preference comes closest to the ideal ―rational man‖ theory. Individuals who prefer

94

thinking look at cost-benefit tradeoffs. Because, managing money is impersonal to them,

they enjoy the challenge. They can create systematic plan for their financial well-being.

Those with a feeling preference make decisions by taking the feelings of other people

into account. They prefer harmony over clarity and may give up their own comfort to

accommodate others. They make decisions based on the potential impact of these

decisions on people. They select products and choices with a personal emphasis. They try

to please by agreeing with everyone, and they may not ask if they don‘t understand

something.

Judging/Perceiving: Judging and perceiving preferences describe lifestyle orientations.

Judging persons are decisive, planful, and orderly, and find making decisions easy. They

work best when they can plan and then follow the plan. They are time driven, like making

lists, and are generally considered well organized. They love to make decisions and

―getting on with things.‖ People with judging preferences are willing to make decisions

and implement them quickly. They are good at long term planning including retirement

planning.

Those with a perceiving preference are flexible, adaptable, and spontaneous. They like to

keep their options open and find that bringing closure is difficult. They prefer gathering

information to see what a task demands rather than detailed planning. They work best in

last-minute spurts of energy to meet deadlines. Their important characteristics are

curiosity, spontaneity, and responsiveness. They delight in processing and considering

new ideas and information. These individuals are open to many different possibilities and

they look for a wide range of information and ideas. They don‘t like to make systematic

plans and implementing plans is difficult for them.

2.10.11 Temperament Theory

The temperaments describe four unique ways that people interact with the environment to

satisfy their needs. In essence, temperament is best understood as a pattern of consistently

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observable behaviours. According to the father of modern temperament theory, Dr. David

Keirsey (Keirsey & Bates, 1984 257 ) ―temperament determines behaviour because

behaviour is the instrument for getting us what we must have…‖ (p. 30).

Temperament is a powerful tool for understanding how we are motivated to use money to

meet our psychological needs. The temperament model of human behaviour provides us

with great insight into financial behaviour. Because each temperament has a particular set

of natural skills they employ to be effective and satisfied in financial matters, an

understanding of temperament is essential to an understanding of financial behaviour.

Judy McKenna et al. (2003)258 said that ―the MBTI can be used to identify the four

temperaments Idealist, Guardian, Rational, and Artisan‖ (p. 22).

Temperaments and management of money

Guardians are of what might be called the preserving temperament. Guardians have a

sensible and judicious temperament (Montgomery, 2002 259 ). For them money

management is about preserving a comfortable, secure and organized home.

They have natural disposition for: measurement which allows them to gauge how much

time, money and material is necessary to properly maintain their standard of living;

sequential thinking, which allows them to manage their finances in an orderly fashion;

supervision, allows them to check that money is managed in the right way by following

the rules: frugal spending, saving money, minimizing debt, preparing for future; and

caretaking, which allows them protecting and providing for their families and loved ones

(Judy Mcenna et al., 2003260

, p. 24).

257

Keirsey, D. & Bates, M. (1984). Please understand me. Character & temperament types. Del Mar, CA:

Prometheus Nemesis Book Company. 258 McKenna, J., Hyllegard, K. & Linder, R. (2003). Linking psychological type to decision making.

Journal of Finanical Counseling and Planning. Association for Financial Counseling and Planning

Education 14 (1). 19-29. 259 Montgomery, S. (2002). People patterns: A modern guide to the four temperaments. Del Mar, CA:

Archer Publications. 260

McKenna, J., Hyllegard, K. & Linder, R. (2003). Linking psychological type to decision making.

Journal of Finanical Counseling and Planning. Association for Financial Counseling and Planning

Education 14 (1). 19-29.

96

Artisans are part of what might be called the ―doing‖ temperament. Artisans have a spur-

of-the moment and playful temperament (Montgomery, 2002). For them, management of

money is about having the freedom to do what feels good. They are skilled in tactics,

reading the immediate situation and making instant decisions to accomplish the purpose.

They have natural disposition for: adaption, which allows them to make right financial

adjustment to deal with unforeseen situation; contextual thinking, which allows them to

understand the urgency of the immediate moment as it relates to their finances;

promotion, which allows them how money can be used to advance and accomplish the

interest; and performance, which allows them getting things to be done as expediently as

possible (Judy Mcenna et al., 2003, p. 24).

Idealists are apart of what might be called the inspiring temperament. Idealists have an

insightful and fervent temperament (Montgomery, 2002). For them, money management

is about cultivating relationships, growing personality and helping others to achieve their

potential.

They have natural disposition for: interpretation, which allows them understanding the

meaning of other‘s behaviour; integrative thinking, which allows them seeing how things

come together; counseling, which allows them seeing how others can help themselves;

and revelation, which allows the insight into underlying motives and desires (Judy

Mcenna et al., 2003261

, p. 25).

Rationals apart of what might be called the achieving temperament. Rationals have an

ingenious and theoretical temperament (Montgomery, 2002). For them, money

management is acquiring necessary competence to understand, explain and predict, and

therefore controlling financial forces that affect their lives.

261 Ibid. p. 25

97

They have natural disposition for: analysis, which allows them to make calculations by

distinguishing components and discerning their interrelationships; differential thinking,

which allows them to see differences, categories, classifications, functions; designing,

allows them to think on all components for plans; and Marshalling, which allow them to

lead, to guide and to rearrange plan components in the necessary order (Judy Mcenna et

al., 2003262

, p. 25).

The above discussion shows that individuals are not rational with regard to any financial

behaviour displayed by them. After presenting the theoretical background for various

financial behaviours displayed by the individuals in this section, the researcher has

proceeded further with the review of various studies, which has attempted to establish the

relationship between financial literacy and financial behaviour. The review of these

studies is presented in the next section.

2.11 Studies on Financial Literacy and Financial Behaviour

This section discusses the findings of past studies; those have attempted to find out the

relationship between financial literacy of individuals and various financial behaviours

displayed by them. Empirical research studies indicate that both economic and

psychological factors are associated with various financial behaviours of individuals,

such as, cash flow management, saving, investment and credit behaviours. Researchers

from diverse fields have contributed to the literature on consumer financial behaviour.

Among them, consumer economists have conducted the research studies to identify

association of financial literacy/education with financial behaviours of individuals. The

in-depth discussion of these studies is presented below.

2.11.1 DeVaney, Gorham, Bechman and Haldeman (1996)

262 Ibid. p. 25

98

DeVaney, Gorham, Bechman and Haldeman (1996263) conducted an experimental study

to examine cash flow and credit use three months after participants completed a series of

women's financial information workshops. The results showed that 24% of the

participants started to set up bill payment system as a practice after attending the

workshop. This study found that age was positively related to the probability of using bill

paying system (p. 75). For creating and maintaining an emergency fund, 44% of the

respondents started the practice after getting financial knowledge. Regarding obtaining

credit, 22% of respondents reported making a change in obtaining credit on their own

name. The only variable that was significantly related to adoption of this financial

behaviour was marital status. Those not married were less likely to adopt this behaviour.

One third of the participants indicated that they limited the number or use of credit cards

after completion of workshop. While four out of ten participants began to save regularly

or increased regular saving (p. 76).

2.11.2 Berhiem, Garrett & Maki (1997)

Berhiem, Garrett & Maki (1997 264 ) examined the effects of mandated financial

curriculum in schools. They attempted to determine whether mandated financial

education across the states and over the time in high school had any long term behaviour

effect on adult decisions regarding savings. The data were collected in the month of

November 1995, from the nationally representative sample of respondents between the

ages of 30 and 49. By using regression analysis on variables related to consumer

education in high school and adult financial behaviour, their results have shown mandates

significantly increase the exposure to financial education, and has positively raised the

rates of saving (a flow variable), and hence accumulate more wealth (a stock variable)

during the adult lives (p. 29). The results indicated that while the effects of this mandate

have been significant, but the effect is gradual rather than immediate. They also found

that the self reported rates of saving rise significantly with education and earnings. The

263 DeVaney, S. A., Gorham, E. E., Bechman, J. C., & Haldeman, V. (1995). Saving and investing for

retirement. Family Economics and Resource Management Biennial, 1, 153-158. 264

Bernheim, D., Garret, M. & Maki, D. (1997). Education and saving: The long term effects of high

school financial curriculum mandates. NBER Working Paper Series: Working Papar No. 0685, National

Bureau of Economic Research, Cambridge, MA.

99

results also show that individuals who received personal finance instructions had a saving

rate 1.5 precent greater than individuals who received no instructions, and wealth is

increased by an amount equal to earnings for one year within 15 to 20 years after

graduation from high school. They also concluded that financial education can be used to

stimulate personal savings (p. 30).

2.11.3 Boyce and Danes (1998)

Boyce and Danes (1998 265 ) have introduced the curriculum on Personal Financial

Planning Program for school children in the NEFE High School Financial Planning

Program (HSFPP). The curriculum is a collaborative effort between the National

Endowment for Financial Education (NEFE), the USDA (United States Department of

Agriculture), and the Cooperative State Research, Education, and Extension Service

(CSREES)—the federal partner of the Cooperative Extension System. It includes an

extensive instructor‘s manual, student workbook, and student personal financial portfolio

which are provided free by NEFE. The curriculum acquainted the students with basic

financial planning concepts and illustrated how these concepts apply to everyday life.

The goal of the curriculum was to increase the financial planning literacy of teens. The

curriculum was divided into seven units: (1) providing an introduction to the financial

planning process, (2) explaining the relationship between career/work factors and earning

potential, (3) developing a personal spending/savings plan, (4) using and managing credit

effectively, (5) describing risk management techniques and explaining the importance of

protecting their assets, (6) explaining the importance of saving and investing and the

benefits of utilizing the time value of money into their savings plans, (7) completing the

personal financial plan. 434 schools were covered under this study. After three months,

the results of the program evaluation found that teaching financial literacy through the

NEFE curriculum has a positive impact on students‘ financial management knowledge,

behaviour and self-efficacy. For all questions, there was a statistically significant increase

in financial behaviour, knowledge, and self-efficacy questions immediately after

265 Boyce, L. & Danes, S. M. (1998) Evaluation of the NEFE high school financial planning program.

Denver CO: National Endowment for Financial Education.

100

participating in the program. The area where the most students increased in knowledge

was in understanding the cost of credit. When investigating the total gains in financial

knowledge, behaviours, and self-efficacy across the 13 questions, 86% of the students

showed an increase in financial knowledge or behaviours. Greater percentages of students

reported that they ―almost always‖: compare prices when shopping (44.5%), set money

aside for future needs or wants (40.5%), and repay the money they owe on time (60%). In

the follow-up, students reported ―almost always‖ knowing the cost of buying on credit

approximately 43 percent of the time. Finally, about 76 % of the students reported that

they ―almost always‖ felt as though the way they managed their money would affect their

future. 58% said they had changed spending habits and 56% said they had changed

saving habits. More than one-third of students (39%) reported that they had started saving

money 3 months after completing the HSFPP. 13.8% (1.0% of 418) reported that they

have now started saving. For determining the saving corpus, a large proportion of

students (38%) reported that they decide on a specific percent or amount of earnings to

save while many students (28%) reported to save only when they had a specific purchase

to make. Nearly one third of students (31%) reported that the most important financial

planning activity they had taken on since participating in the HSFPP was establishing a

savings account.

2.11.4 German and Kim (1999)

German and Kim (1999 266 ) conducted a study to investigate the effectiveness of

workplace financial education at one of plants owned by a Southeastern chemical

production company.

Differences and similarities between participants and nonparticipants in the financial

workshops were explored. The objectives of the workshop were to assess the workers‘

perception of financial wellness and personal financial behaviours, to measure changes in

workers‘ personal financial behaviour who participated in the workshops and to obtain

266 Garman, E. T., Kim, J., Kratzer, C. Y., Brunson, B. H., and Joo, S. (1999). Workplace financial

education improves personal financial wellness. Financial Counseling and Planning, 10 (1), 89- 94.

101

self-reported measures of health and job performance ratings. Workshop participants

reported a positive change number of personal financial behaviour as a result of the

education received. Three-quarters (75%) of the workshop participants reported that

―they have made better financial decisions since attending the workshops‖. Seventy-five

percent of the participants related that they were more confident in making investment

decisions. Seventy percent reported they changed their investment strategy by

appropriately diversifying or being more aggressive in their investment choices. Fifty-six

percent of participants agreed that ―their financial situation had improved because of the

financial education.‖ Almost half (45%) of the workshop participants increased the

amount of contribution to the employer‘s 401(k) plan. Thirty-four percent workers agreed

that they started for contributing towards the 401(k) plan as a result of the financial

education workshops (p. 85). It was also found that those who participated in the

workshops tended to have credit under control, a budget and a financial plan and had

improved their financial situation. The overall findings suggest that the most workshop

participants took positive actions to improve their financial well being after they receive

financial education.

2.11.5 Clark et al. (2003)

Clark et al. (2003 267 ) found that financial education seminars have an effect on

individuals‘ retirement goals and saving behaviour. They studied the responses to

questionnaires distributed and collected from 60 TIAA- CERF financial education

seminars held at educational institutions and non-profit organizations between March

2001 to May 2002. In these seminars, participants completed a survey on retirement goals

and after being asked to attain a one-hour financial education seminar, they filled up a

second questionnaire and checked whether their retirement goals have changed? Analysis

of the results showed that 34 percent of the participants changed either their retirement

income goal or their retirement age goal in response to the seminar. 90 percent of

respondents reported that they anticipated making changes to their retirement saving

267

Clark, R. et al., (2003, March). Financial education and retirement savings. Paper presented at the

conference on Substantial Community Development: What Works, What Does‘t, and Why, sponsored by

the Federal Reserve System, Washington, D.C.

102

plans. The researcher concluded that the provision of financial information has an

important effect on saving for retirement.

2.11.6 Hilgert, Hogarth and Beverly (2003)

The study of Hilgert, Hogarth and Beverly (2003268

) is published in Federal Reserve

Bulletin, utilized the discipline of behaviour economics as a framework for exploring the

differences in consumer knowledge and consumer behaviour, and also explained how

these two are connected (p. 320). They focused on four primary activities of financial

management: cash flow management, credit management, saving and investment. The

data was collected from University of Michigan‘s Monthly Surveys of Consumers and

the Survey of Consumer Finances conducted in November and December 2001 in order

to assess 1) financial literacy of adults and 2) effect of this financial literacy on their

financial behaviours. Eighteen financial management behaviours were reported on by

consumers, like basic skills while managing money i.e. cash-flow management, saving to

and more sophisticated skills such as investment and credit behaviours. Information about

their use of 13 different financial products was also provided. When using an index,

where behaviours were divided into classifications of low, medium, and high, they found

that financial behaviours are hierarchical. This means that individuals with limited

amounts of cash should engage in practices that manage their cash flows, but not in

saving or investing.

They found there is a direct correlation between financial knowledge and behaviour,

although the direction of the causality is unclear. Those who score higher on financial

literacy tests were more likely to follow recommended financial practices as well as more

likely to engage in recommended financial behaviour. They concluded that increased

index scores for investment, saving, and credit management practices are partially

contributable to understanding and being knowledgeable about investment, savings, and

credit respectively. According to this data, improvements in individuals‘ financial


between knowledge and behaviour. Federal Reserve Bulletin, 89 (July): 309-322.Washinton, D.C.

103

management practices are directly related to the amount of knowledge and experience

possessed (p. 321).

2.11.7 Grable and Joo (2004)

Grable and Joo (2004 269 ) conducted an exploratory study on understanding the

determinants of financial satisfaction. They have reviewed the various determinants of

the financial satisfaction and developed a framework of financial satisfaction. They found

numerous direct, indirect and total effects in their study. They determined that education,

financial knowledge, financial risk tolerance, financial solvency, financial behaviours and

financial stress levels had a direct effect on the financial satisfaction.

2.11.8 Grable and Joo (2004)

Grable and Joo (2004270

) analyzed effect of environmental and biopsychosocial factors

on financial risk tolerance of an individual. The objective of the research was to test the

effects of demographic, socioeconomic and psychological variables on financial risk

tolerance among the college faculty and staff members, using environmental (age,

gender, racial background, birth order, self-esteem, Type-A personality, and financial

satisfaction) and biopsychosocial (income, net worth, financial knowledge, home

ownership, education, marital status) factor classifications. The intent of test was to

determine whether environmental and biopsychosocial factors play a role in determining

the person‘s tolerance for financial risk, and if it confirmed, when and which factor

appeared to be the most important. The study was premised on Irvin‘s (1993271) risk

taking behavioural model. Financial risk tolerance is defined as the willingness to engage

in ―behaviours in which the outcomes remain uncertain with the possibility of an

identifiable negative outcome‖ (Irvin, 1993, p. 11). Findings derived after analyzing data

269 Grable, J.E., & Joo, S. (2004). Environmental and biopsychosocial factors associated with risk tolerance.

Financial Counseling and Planning 15(1), 73–82. 270

Grable, J. E. & Joo, S. (2004). Environmental and biopsychosocial factors associated with financial risk

tolerance. Financial Counseling and Planning 15(1), 73–82. 271 Irwin, C. E. (1993). Adolescence and risk taking: How are they related? In N. J. Bell & R.W. Bell

(Eds.), Adolescent risk taking. Newbury Park, CA: Sage.

104

collected from the sample (N= 406) of faculty and staff from two universities, indicated

that education, marital status, net worth, financial knowledge, household income, and

self-esteem were significantly related to financial risk tolerance. Among all of these

significant factors, except self-esteem, were environmental factors, while self-esteem

represented only one significant biopsychosocial factor. The study concluded that

respondents who have a higher net worth, a high level of education, high household

income and more financial knowledge tend to exhibit a greater level of preference for

financial risk. While, in terms of biopsychosocial factors, self esteem is related positively

to financial risk tolerance. Study also confirmed that environmental factors influence risk

tolerance more directly than biopsychosocial factors.

2.11.9 Mandell (2005)

Mandell (2005272) used the data collected by The Jumpstart Coalition and conducted a

survey with an objective to find out financial literacy of high school students. The survey

contained 31 questions and distributed to a sample of approximately 4,000 high school

students every two years. The results of the survey have proven that students are fairly

financially illiterate, which has continued in a downward trend since then. Mandell

evaluated the survey results to determine the correlation between financial literacy and

propensity to save. This study found that financial education does contribute, although

only slightly, to measures of financial literacy and financial education does positively

affect the savings. Saving also appears to have some impact, however small, on the

propensity to save. Although the study produced unusual results, the overall conclusion

of the study was that financial education affects propensity to save without necessarily

improving financial literacy. In other words, students who take courses dealing with

personal finance may emerge with little improvement in financial literacy, but they may

end up more savings oriented than students who have not had a course. Mandell also

concludes that even if financial literacy does matter, educators must first determine which

272

Mandell, L. (2005) Financial Literacy – Does it Matter? The Jumpstart Coalition for Personal Financial

Literacy. Washington D.C.: Retrieved on December 2008 from: http://www.jumpstart.org/ download.cfm.

105

areas are of the most important to teach and the appropriate time tables for educating

students.

2.11.10 Kim (2007)

Kim (2007 273) examined the impact of a Cooperative Extension workplace financial

education program on a selected group of university employees. A pre- and post- survey

design was used. The University of Maryland Cooperative Extension offered four two-

hour workshops for 97 University employees from the summer and fall of 2002 to the

spring and fall of 2003. The workshop curriculum was consisted of eight modules, such

as financial decision making/goal setting, financial record organization, cash

management, credit management, risk management, investment, retirement planning, and

estate planning. The study examined the influences of the program on university

employees‘ self-assessed financial knowledge, financial behaviours, and perceived

financial well-being. The data collected during pre- and post-assessment found that

participants made significant improvements in financial knowledge, financial behaviours,

and perceived financial well-being. The present study used the Human Behaviour model

of Ajzen and Fishbein (1980274) where knowledge and attitudes are related to individual‘s

beliefs and changes in beliefs are reflected in behaviours. Based on Ajzen and Fishbein‘s

model, Kim (2000275) developed a framework conceptualizing that workplace financial

education could positively change financial knowledge and financial behaviours, which

in turn could improve financial well-being. Further, workplace financial education could

impact employees‘ absenteeism and job satisfaction by improving their financial well-

being. Overall, participants perceived that their financial well-being improved as a result

of the workshops, which was similar to Hira and Loibl‘s (2005276) study. Although the

mean scores for saving for retirement in the financial behaviour scale did not change,

273 Kim, J. (2007). Workplace financial education program: Does it have an impact on employees' personal

finances? Journal of Family and Consumer Science, 99(1), 43-47. 274 Ajzen, I. & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood

Cliffs, NJ: Prentice-Hall. 275 Kim, J. (2000). The effects of workplace financial education on personal finances and work outcomes.

Doctoral Dissertation, Blacksburg: Virginia Polytechnic Institute and State University. 276 Hira, T. K. & Loibl, C. (2005). Understanding the impact of employer-provided financial education on

workplace satisfaction. Journal of Consumer Affairs, 39(1), 173-194.

106

people felt more secure about their personal finances for retirement after the workshops.

Further, although satisfaction with their current financial situations did not change

significantly, their financial stress had decreased and their feelings of retirement security

and general perceived financial well-being improved. The results suggest that workplace

financial education not only impacts retirement planning, but also perceived financial

well-being. Studies have found that employees‘ subjective financial well-being influences

their absenteeism, job satisfaction, and organizational commitment.

2.11.11 Maarten van Rooji et al. (2007)

For better understanding of financial literacy and its relation to financial decision making,

Maarten van Rooji, Annamaria Lusardi and Rob Alessie (2007277) designed two modules:

1) Basic financial literacy and 2) Advanced financial literacy, covering the questions to

measure numeracy and basic knowledge related to the working of inflation and interest

rates, as well as questions to measure more advanced financial knowledge related to

financial market instruments (stocks, bonds, and mutual funds) before entering into the

stock market. They used the data from the 2005 DNB (De Nederlandsche Bank)

Household Survey (DHS). This data set was representative of the Dutch population, and

was contained over 2,000 households. This study found that lack of financial literacy

correlates with investors‘ decisions to participate in the stock market and also financial

literacy matters for stock market ownership, even after controlling a large set of

demographic variables, income and wealth. The estimates are also sizable: A one-

standard deviation increase in advanced literacy raises stock market participation by more

than eight percentage points (p. 16). Thus, overall study concluded that stock ownership

increases sharply with the financial literacy (p. 15).

2.11.12 Luigi and Japelli (2008)

277 van Rooij, M., Lusardi, A., & Alessie, R. (2007, October). Financial literacy and stock market

participation. Dartmouth College, MRRC Working Paper 2007-2162.

107

Luigi Guiso and Tullio Japelli (2008278) attempted to find out a correlation between

financial literacy and portfolio diversification by using the data of Unicredit Clients‘

Survey conducted between June and September 2007. They have developed a sample of

Italian clients possessing at least 10,000 euro of financial wealth of the Unicredit Group.

The survey collected data from the respondents of 1686 individuals having a checking

account in one of the banks of Unicredit Group. The objectives of the study were to

analyze the different levels of financial literacy, with reference to the information

required to choose among different sets of assets and understand the meaning of

diversification. After analyzing the impact of financial literacy and investors‘

characteristics on portfolio diversification, they found that measures of financial literacy

are strongly correlated with the degree of portfolio diversification, and infer that the

evidence is consistent with explanation of under diversification based on investors‘

limited financial literacy. They have given four types of explanations for the lack of

diversification. One, the limited diversification reflects some frictions in otherwise

traditional portfolio models: high transaction cost, search cost, small portfolio size and

constraints to buy in round lots. This approach stresses that under-diversification is a

rational choice, where individuals trade-off the benefits of diversification against the

costs of achieving it. The exact mechanisms through which these frictions operate vary:

they can restrict the ability of investors to hold a large number of assets (Perraudin and

Sorensen, 2000279), limit their information processing capacity (Van Nieuwerburgh and

Veldkamp, 2007280), or affect the way they value outside job options (p. 4). Second, they

argued that diversification may reflect behavioural biases (p. 4). And third, investors may

develop preferences or attractions towards certain types of stocks (p. 5). And lastly, the

poor financial literacy is a fourth important factor associated with lack of diversification.

The individuals with poor financial sophistication may undervalue the benefits of

diversification or ignore them altogether (p. 6).

278 Luigi, G. & Jappelli, T. (2008). Financial literacy and portfolio diversificaition. CSEF Working Papers

Series, Working paper No. 212, Centre for Studies in Economics and Finance (CSEF), University of

Naples, Italy. 279 Perraudin, W. R. & Soreson B. E. (2000). The demand for risky assets: Sample selection and household

portfolios. Journal of Econometrics, 97, 117-144 280 Nieuwerburgh, S.V., & Veldkamp, L. (2007). Information acquisition and under-diversification. Stern

School of Business, New York University, Mimeo.

108

2.11.13 Hussain et al. (2009)

Hussain et al. (2009281) studied the level of financial literacy of UAE individual investors

who invest in local financial markets and examined the relationship between financial

literacy and the influence of the factors that affect the investment decision.. The data

were collected from 290 national investors. The study found that financial literacy of

UAE investors is far from the needed level. The financial literacy level was found to be

affected by income level, education level and workplace activity. High-income

respondents hold high educational degrees, and those who work in the field of

finance/banking or investment had as expected a higher financial literacy level than

others, whereas, financial illiteracy exists regardless of the age of the respondents. A

significant difference in the level of financial literacy was found as well between the

respondents according to their gender. Specifically, women possess a lower level of

financial literacy than men. The study also concluded that there is a relationship between

financial literacy and investment decisions.

2.11.14 Seth et al. (2010)

Seth et al., (2010282) assessed the level of financial literacy among the investors of Delhi

and National Capital Region. The study attempted to analyze the relationship between

financial literacy and other factors like age, income, and education. The study indicated

that the financial literacy of investors in Delhi and NCR was different for different

financial instruments. Around 96% of them have savings account in the banks, but the

mere acquaintance with banks is not adequate, as only around 30% had knowledge about

National Savings Certificate & Public Provident Fund. While 98 % of the investors knew

about Life Insurance, only about 45% preferred Life Insurance as the most effective

financial instrument, which would be helpful at the time of contingencies. Around 92 %

281 Hussein A. H., Al-Tamimi & Al Anood B. K. (2009). Financial literacy and investment decisions of

UAE investors. The Journal of Finance, 10(5), 500- 516. 282 Seth, P., Patel, G., and Krishnan, K. K. (2010). Financial literacy and & investment decision of Indian

investors – A case of Delhi & NCR.

109

of the investors knew about Mutual Funds but only 24 % preferred them. Financial

literacy is found to be affected by age, income and educational level of the individuals.

High-income respondents had high financial literacy than lower income people. The

study also revealed that people consider Life Insurance as the most effective financial

instrument followed by Fixed Deposits in banks. It was also found that most of the people

relied on telecast in the T.V channels or advertisements put out in the newspapers and

magazines to learn about financial products followed by ―advice‖ from friends. But,

while investing in share market, around 21% people relied on brokers.

2.12 Conclusion

The review of literature presented in this chapter is evidence for that financial literacy

levels possessed by the individuals among the various countries is low irrespective of the

stage of development of the country. Among them, several studies have also established a

relationship between financial literacy and demographics of an individual. While, the

studies done by consumer economists attempted to establish the relationship of financial

literacy with various financial behaviours, as an outcome of financial education. The

studies documented in this chapter shows a low level of financial literacy and lack of

financial information/education affect the ability to perform responsible financial

behaviour. In the context of Indian Economy, the researcher has proceeded further with

an exploratory research to find out whether the investors in state of Gujarat, which is one

of the most progressing states of India does possess the sufficient level of financial

literacy and does it have any impact on their investment decision. The next chapter

discusses the research methodology adopted for this study.

Research

Methodology

Chapter 3

110

3.1 Introduction

3.2 Research Gap

3.3 Objectives of the study

3.4 Scope of the study

3.5 Research Methodology

3.5.1 Research Design

3.6 Sampling Design

3.6.1 Sampling Technique

3.6.2 Population

3.6.3 Sampling Unit

3.6.4 Sample

3.6.5 Sample Size

3.7 Data collection

3.7.1 Secondary Data

3.7.2 Primary Data

3.8 Research Instrument

3.9 Description of variables

3.9.1 Description of demographic and socio-economic variables used

under study

3.9.2 Description of variables used as investmentalternatives

3.9.3 Description of variables used as preferred source of

information used under study

3.9.4 Description of variables influencing investment decision used

under study

3.10 Coding of Variables

3.11 Data analysis

3.11.1. Univariate techniques

3.11.2 Bivariate techniques

3.11.3 Multivariate techniques

111

3.11.4 Available Methodologies to measure Financial Literacy

3.11.5 Methodology used to Measure Financial Literacy for Present

Study

3.12 Hypotheses of the study

3.13 Conclusion

112

3.1 Introduction

Research is a scientific and systematic search for pertinent information on a specific

topic283

. The Advance Lerner‘s Dictionary of Current English lays down the meaning of

research as ―a careful investigation or inquiry especially through search for new facts in

any branch of knowledge‖284

. Before executing any research study, its research

methodology should be laid down explicitly. Research methodology includes various

steps that are generally adopted by a researcher in studying his/her research problem

along with the topic logic behind it. Research methodology depends, to a large extent, on

the target population, and how easy or difficult to access it is. The second factor which

influences it is, of course the importance of the decision which is taken based on the

research. Major parts of the research methodology are problem statement, research

design, sampling plan, questionnaire design, field work plan and analysis plan285

. The

current chapter provides an in-depth view of research methodology discussing on how the

researcher has carried out the present research.

3.2 Research Gap

On the basis of literature review done in the previous chapters, three general conclusions

have been drawn by the researcher.

1. There is a low level of financial literacy among the various demographic groups of the

citizens of different countries, irrespective of stage of the economic development of a

country.

2. There is a strong relationship between financial literacy level and demographic factors.

The literature review supported that there is a strong relationship between financial

literacy levels and demographic factors such as age, gender, education, income level and

work experience.

283 Kothari, C. R. (1999). Research Methodology: Method and Techniques. New Delhi: New Edge

International Publication. p. 1. 284 The Advanced Learner‘s Dictionary of Current English, Oxford, 1952, p. 1069. 285 Nargundkar R. Marketing Research- Text and Cases (2nd Revised ed.), New Delhi: TATA McGraw Hill,

26.

113

3. There is a relationship between financial literacy of individuals and their financial

behaviors.

On the basis of above discussion, the researcher found out a gap which exists in the

previous research works presented here. The present study attempts to study the level of

financial literacy among investors of Gujarat State, who invest in the domestic financial

markets. The present study has focused on following demographic and socio economic

factors of the investors.

Age,

Gender,

Education,

Monthly Income,

Stage of family life cycle,

Employment Structure,

Type of workplace Activity,

Number of years of work experience,

Number of years of Investment Experience,

Number of times individual shop around and

Risk Tolerance Level.

This study has also examined the relationship of these factors on financial literacy level

of investors and the impact of financial literacy level on their monthly spending to

monthly income ratio, monthly saving to monthly income ratio and investment decision.

3.3 Objectives of the study

The broad objective of this research is to study the level of financial literacy of investors

of Gujarat State and its impact on their investment decision.

Specific Objectives of the research are:

114

1. To explore the financial literacy level among the investors of Gujarat State.

2. To study the relationship between demographic and socio economic factors of

investors and their financial literacy level.

3. To study the investors‘ preference towards various sources of information for

investment.

4. To study the difference between preferences for the selected informative variables

and their influence on investment decision under study.

5. To study the relationship between financial literacy level of investors and their

monthly expenditure to monthly income ratio of investors.

6. To study the relationship between financial literacy level of investors and their

monthly saving to monthly income ratio.

7. To study the impact of financial literacy level on investment decision of investors.

3.4 Scope of the study

As mentioned in the objectives of study, the researcher has explored the level of financial

literacy among the investors of Gujarat State. After doing an in-depth study of available

literature on chronological developments taken place while defining the term ―financial

literacy‖, the researcher has conceived the following operational definition of ―financial

literacy‖, which defines the scope of the term for the present study.

Financial Literacy:

Financial literacy is a set of skills and knowledge that allows an investor (individual) to

understand

- the financial principles that individual needs to know to make informed decisions

and

- the financial products that impact individual‘s financial well-being.

115

Here, financial literacy is concerned with the understanding of basic financial concepts,

principles, skills and ability to understand key financial products, to make good financial

choices.

To explore the level of financial literacy, basic financial literacy and advanced financial

literacy are used. The in-depth description of the scope of the terms basic and advanced

financial literacy is mentioned as follows.

A. Basic Financial Literacy (Financial Competence)

Knowledge and understanding of basic financial concepts, principles and

ability to understand key financial concepts.

1 Scope of the term investment 2 Financial worth

3 Concept of disposable income 4 Types of Bank accounts

5 Numeracy 6 Compounding

7 Concept of inflation 8 Time value of money

9 Functioning of stock market 10 Diversification

11 Risk return trade off 12 Risk

13 Risk return trade off of two assets 14 Relationship between investment time

horizon and asset growth

15 Relationship between investment

time horizon and fluctuation

16 Asset al.location

17 Relationship between interest and

asset prices

18 Consumer rights and responsibility

19 Regulatory body as a part of market

structure

20 KYC

B. Advanced Financial Literacy (Product Literacy)

Understanding the basic features of various financial services/investment

instruments

available to the individual investor in Indian Financial Systems.

116

For advanced financial literacy, 30 questions were asked to the respondents covering:

3.5 Research Methodology

Research methodology is a way to systematically solve research problem (Kothari,

1999286

). A system of models, procedures and techniques used to find the result of a

research problem is known as Research Methodology (Panneerselvam, 2010287

).

3.5.1 Research Design

Research design is an arrangement of data collection and analysis of data in a manner that

aims to combine relevance to the research purpose. It is a blue print for the collection,

measurement and analysis of data.

For this study Exploratory and Descriptive research design methods have been used,

wherein researcher has explored the financial literacy level of investors and then

described the impact of financial literacy level on investment decision of investors. Both

the types of source of data primary and secondary were used. The data collection method

is discussed in detail in the following sections.

3.6 Sampling Design

286 Kothari, C. R.(1999). Research Methodology: Method and Techniques (2nd revised ed.). New Delhi:

New Edge International Pvt. Ltd., p. 8. 287 Panneererselvam, R. (2010). Research Methodology (8th ed.). New Delhi: Prentice-Hall India Ltd., p.2.




7. Mutual Funds 8. Debentures and Bonds

9. Post office Monthly Income scheme 10. Insurance Plan

117

Sampling design is a definite plan for obtaining a sample from a given population.

Sampling plan means a method, decided before the survey is undertaken, of selecting the

objects out of the universe. It refers to the technique or the procedure a researcher adopts

in selecting a sample and the sample size.

3.6.1 Sampling Technique

Sampling techniques are broadly divided into two groups as probability sampling

techniques and non-probability sampling techniques. For the current study, non-

probability convenient sampling technique is chosen. In convenient sampling technique,

the researcher chooses the sampling units as per his/her convenience.

3.6.2 Population

For any research study, to identify or decide the target population is one of the most

important things. Target population is defined as a specific group of people or objects for

which the data can be gathered or observations made to develop required data structure

and information288

. As this study has been done in the state of Gujarat of India, the retail

individual investors289

(above the age of 18 years) of Gujarat State are considered as a

population for this study.

3.6.3 Sampling Unit

Sampling unit is an object for which the data being gathered. For this study, all

households in the state of Gujarat who make investments in financial instruments are

considered as sampling unit.

288

Hair, Bush and Ortinau, Marketing Research- Within a Changing Information Environment (2nd ed.).

Tata McGraw Hill Publication, p 43. 289

―Retail individual investor‖ means an investor who applies or bids for specified securities for a value of

not more than two lakhs rupees. This definition is given in Securities and Exchange Board of India (Issue

of Capital and Disclosure Requirements) Regulations, 2009 (Amended), dated August 26, 2012, p. 4.

118

3.6.4 Sample

For this study sample is an Individual.

3.6.5 Sample Size

Total sample size of 385 investors in the state of Gujarat is considered for the study.

During data collection, proper care was taken to collect the data in such a way that it

covers the entire state of Gujarat. The justification for sample size determination is given

below.

Following formula can be used to determine sample size (Nargundkar, 2003290

).

𝑛 = 𝑝 1 − 𝑝 𝑍

𝑒

2

𝑛 = 0.50 1 − 0.50 1.96

0.05

2

Where,

N = Sample Size

Z = Z value from the standard normal distribution for the confidence level desired

by the researcher. For this study, the researcher has assumed 95 percent

confidence level. Then from the standard distribution tables, the Z value is 1.96.

p = Frequency of occurrence of something expressed as proportion (0.50).

290 Nargundkar, R. (2003). Marketing Research: Text and Cases (2nd ed.). New Delhi: TATA McGraw Hill

Publication, pp. 94-95.

𝑛 = 385

119

E = Tolerance error. This can be decided by the researcher. For this study, the

researcher as assumed tolerance error 0.05.

Applying above formula, the sample size comes to 385. Hence, researcher has collected

the primary data from 385 respondents.

3.7 Data collection

For this study both primary as well as secondary data sources are used.

3.7.1 Secondary Data

To get insight into the research area and to develop the theoretical framework and

hypotheses, the information was collected from various books, magazines, journals,

newspapers, web sites, research projects, reports published by Government and private

research firms at national and international level. Speeches and lectures of officials of

various governmental authorities and policy makers around the world were also used as

secondary data sources.

3.7.2 Primary Data

A detailed Performance Test and Questionnaire were prepared and administered on

investors in the State of Gujarat. With the help of these, personal (face to face) interviews

of the respondents were performed, because of the advantages of this method over other

methods. By personal interviewing, the researcher gets some other information pertaining

to the respondent. Sometimes, if the respondent has any query/doubt, it can be traced by

the researcher or interviewer.

Total sample size of 385 investors in the state of Gujarat is considered for the study.

During primary data collection, proper care was taken to collect the data in such a way

that it covers the entire state of Gujarat. For the purpose of primary data collection, the

120

researcher has approached various investors‘ associations operating in the different cities

of Gujarat with the objective of investors‘ awareness. The researcher has approached the

individual retail investors (respondents) at various investors awareness programmes

conducted by these associations in collaboration with SEBI and/or The Bombay Stock

Exchange Ltd. under the Investor Education and Protection Fund (IEPF). The researcher

has distributed and collected the filled up questionnaires from the respondents, before the

investor awareness programmes would begin. The investors were invited to attend these

programmes by an open invitation given as an advertisement in the newspapers.

After the collection of primary data, it was found that some of the questionnaires were

not filled up properly or some of the questions were not attempted. Such questionnaires

were discarded and new questionnaires from other investors were again collected.

3.8 Research Instrument

The survey was developed to investigate the financial literacy level of investors and its

impact on investment decision. To serve this objective, the research instrument was

divided into four sections. The details of which are discussed in the next section.

Instrument Construction:

Primary data are the most important source for this study as it is given by the investors.

Performance Test and Questionnaire were used as a research instrument to collect this

data. So, preparation of Performance Test and Questionnaire is the most important stage

for this study. Initially, preliminary research instrument was prepared based on in-depth

literature review in the same and/or similar field. Then the research instrument was sent

to a total of 16 experts at national and international level. Out of which, eleven experts

were from finance disciplines in the academic field, four experts were senior officials of

Securities and Exchange Board of India (SEBI), two experts were academicians in U.K.

and U.S.A, and one expert who is a policy maker on financial literacy among OECD

member countries, Organization of Economic Cooperation and Development (OECD).

121

The changes were incorporated in the research instrument as suggested by the experts and

then pilot testing of this modified research instrument was performed. Some drawbacks

were identified from the pilot testing. After eliminating these drawbacks and simplifying

language, final research instrument was prepared for the study. The research instrument

was not only in English, but, considering that language should not be a barrier to measure

financial literacy level of investors and its impact on investment decision, the whole

research instrument was translated into regional language of the state of Gujarat, i.e.

Gujarati. The translated version of the data collection instrument was sent to reviewers

who are subject experts in the field of Gujarati language. As per their suggestions, some

of the basic words and sentences were modified; keeping in mind that the ultimate crux

of the variables (to be studied) would not be changed.

The final research instrument was divided into four sections. Out of which Section A and

section B comprised of performance test on objective type and true/false type questions

(total 50 questions) based on basic financial literacy (20 questions) and advanced

financial literacy (30 questions) respectively. The respondents‘ overall performance in

these two sections has generated result of financial literacy level possessed by him/her in

terms of score. To measure the literacy level, the score as a percentage of correct answers

(Lyons, 2007291

) is taken into consideration (Detailed discussion on this has been done in

the next section of the same chapter). Section C comprised of questionnaire for

investment decision and risk tolerance level and the last section of the research

instrument was section D which consisted of questions based on demographic and socio-

economic variables. The research instrument follows a specific format and each question

belonging from a particular section of a data collection tool with its objective is briefly

discussed as under.

Section A: To measure basic financial literacy level (skills, knowledge and

understanding of basic financial concepts, principles and numeracy that individual should

posses), 20 questions were asked to the respondents. Out of these, 13 questions were

291 Lyons, A., Rachlis, M., & Scherpf, E. (2007). What‘s in a Score? Differences in Consumers‘ Credit

Knowledge Using OLS and Quantile Regressions. Networks financial institute. Indiana University, 2007-

WP-01, retrieved on January 21, 2012 from www.networksfinancialinstitute.org.

122

taken from the scale developed by Maarten van Rooji, Annamaria Lusardi and Alessie

Rob (2008292

). These questions ranging from numeracy, interest compounding, inflation,

time value of money, functioning of stock market, diversification, risk-return trade off of

two assets, risk, money illusion, relationship between investment time horizon and

fluctuation, concept of asset al.location, relationship between interest and asset price. The

rest of the seven questions were based on investment concept, financial worth, disposable

income, understanding of types of accounts, consumer right and responsibility,

knowledge of authority and KYC.

Section B: To measure advanced financial literacy level (knowledge and understanding

of the investment alternatives available to the investors in Indian Financial Systems), 30

questions were framed in this section, on the basis of features of these investment

alternatives available for saving and/or investment. These are as follows:

Section C: The questionnaire comprised of eight questions following the objectives

under study. First two questions were introductory question and had served the two

purposes 1. Identification of a sampling unit and 2. To get the attention of the respondent

to fill up the questionnaire. Out of which the second question was based on the present

investment pattern of investors, where the respondents were given the eight multiple

choices. These are 1) Post office Savings Schemes 2) Insurance and Pension Plans, 3)

Bank Deposits 4) Mutual Funds, 5) Shares, 6) Debentures and Bonds, 7) Real Estate and

292 Van Rooji, M., , Lusardi, A. & Alessie, R. (2008). Financial literacy and stock market participation, in

Financial Literacy, Retirement Provisions and Household Portfolio Behavior by Van Rooji, M. 45-90.




7. Mutual Funds 8. Debentures and Bonds

9. Post office Monthly Income scheme 10. Insurance Plan

123

8) Precious metals (Gold and Silver only). The in-depth description of these variables are

given in Table 3.2. The objective of third question was to know the respondent‘s

preference towards various investment alternatives. For this, the respondents were given

eight multiple choices, which were similar to the previous question. These are 1) Post

office Savings Schemes 2) Insurance and Pension Plans, 3) Bank Deposits 4) Mutual

Funds, 5) Shares, 6) Debentures and Bonds, 7) Real Estate and 8) Precious metals (Gold

and Silver only). The respondents were asked to rank the each investment alternative on

the basis of their preference for investment. The fourth question gives information about

the reasons that restrict the individual for not to invest (This question was asked only to

those respondents who are non-investors). The objective of the fifth question was to

know the respondents‘ investment objectives in the manner of their importance. For this,

seven investment objectives are given to respondents and they were asked to rank each

investment objective on the basis of their importance. These investment objectives are 1)

Saving of Income-tax, 2)Buying/improving home, 3) Child‘s marriage/education/social

ceremonies, 4) Secured retirement, 5) Gift/ donation/ vacation/ pilgrims, 6) To meet

unexpected financial contingencies and 7) To safeguard against inflation/ capital

appreciation. The sixth and seventh questions are rating questions collected on 5-point

Likert scale ranging from the least preferred = 1 to highly preferred = 5 and the least

influence = 1 to highly influence = 5 respectively. The question six is on respondent‘s

preference towards particular source of information while collecting information for

investment decision, which contains sixteen variables and question seven, contains forty

four variables that may influence the respondent‘s investment decision. In questions

seven, the researcher has employed forty four variables modified from that used by

Hussein A. H. (2009293

). The in-depth description of the variables used in question six

and seven are given in Table 3.2 and 3.3 respectively. The last question of this section is

to find out the investment risk tolerance level of the respondent. For this, the scale was

adopted from SEBI‘s financial education material (2010294

) especially developed for

financial literacy initiative in India.

293 Hussein A. H. Al-Tamini & Al Anood B. K. (2009). Financial literacy and investment decisions of UAE

investors. The Journal of Risk Finance, 10 (5). 294Securities and Exchange Board of India (SEBI) (2010). Lessons on financial planning for young

investors. 30-31.

124

Section D: This section focuses on personal information of respondents. The questions

based on city, age, gender, higher level of education attempted, monthly income, stage of

family life cycle, employment structure, type of workplace activity, years of work

experience, proportion of monthly expenditure to monthly income, proportion of monthly

saving to monthly income, years of investment experience and number of times

respondents shop around/ make inquiry while investing are drawn from the previous

research studies done in the field of financial literacy and nearer to it. Table 3.1 shows the

description of demographic and socio-economic variables used in this study.

The questionnaire in English and its translated version in Gujarati language are given in

the annexure.

3.9 Description of variables

The in-depth description of variables used under this study is given below.

3.9.1 Description of demographic and socio-economic variables used under study

Table 3.1 shows the description of demographic and socio-economic variables used under

study.

125

Table 3.1 Description of Demographic and Socio-Economic Variables used Under Study

Variables Scale used to

measure a

variable

Type of

measurement used to

measure a variable

Interval Source

Gender Dichotomous Multiple Choice

Question

All male investors (decision makers)

All female investors (decision makers)

---

Age Nominal Multiple Choice

Question

18-25 years,

26-35 years,

36-45 years,

46-55 years,

56-65 years,

66 years & above.

NCAER-MNYL Report

(2007). How India Earns,

Spends and Saves: India

Financial Protection Survey.

Education Nominal Multiple Choice

Question

Primary,

Secondary,

Higher Secondary,

Graduation,

Post Graduation.

NCAER-MNYL Report

(2007) How India Earns,

Spends and Saves: India

Financial Protection Survey.

Monthly

Income

Nominal Multiple Choice

Question

Upto Rs. 10,000,

Rs. 10,001 to Rs. 15,000,

Rs. 15,001 to Rs. 20,000,

Rs. 20,001 to Rs. 25,000,

Rs. 25,001 and above.

NCAER and SEBI (2011),

How Households Save and

Invest: Evidence from

NCAER Household Survey

Stage of family

life cycle


Question

Young single,

Young married without children,

Young married with children,

Middle-age married with children,

Middle age married without dependent

children,

Older married,

Older unmarried.

Schiffman, L. & Kanuk, L.

(2008). Consumer Behavior.

Ninth Ed. Pearson

Education, Inc. New Delhi.

p. 38

126


measure a

variable

Type of

measurement used to

measure a variable

Interval Source

Employment

structure


Question

Full time salaried,

Part time salaried,

Casual, Self employed,

Housewife, Retired, Unemployed,

Student.

Hussein A. H. et al. (2009)

Type of

workplace

activity


Question

Working in finance/account related

Multiple Choice Question activity,

Not working in finance related activity.


Years of Work

Experience


Question

Less than five,

6 to 10 years,

11 to 20 years,

21 to 30 years,

More than 30 years.


Years of

Investment

Experience


Question

Less than five,

6 to 10 years,

11 to 20 years,

21 to 30 years

More than 30 years.


Monthly

expenditure to

monthly income

ratio


Question

1% to 50%,

51% to 60%

61% to 70%,

71% to 80%,

81% to 90%,

More than 90%.

SEBI-NCAER (2000)

Survey of Indian Investors.

Part A.SEBI.

Table 3.1 Continued

127


measure a

variable

Type of

measurement used to

measure a variable

Interval Source

Monthly saving

to monthly

income ratio


Question

1% to 50%,

51% to 60%

61% to 70%,

71% to 80%,

81% to 90%,

More than 90%.

SEBI (2000). Survey of

Indian Investors. Part A.

SEBI.

No. of times

investor shop

around295

/ make

inquiry while

investing


Question

Zero,

1 to 3,

4 to 6,

More than 6.

ACNeilson (2005). ANZ

Survey of Adult Financial

Literacy In Australia.

Risk Tolerance Nominal Multiple Choice

Question

Lowest risk takers,

Moderate risk takers,

High risk takers,

Highest risk takers.

SEBI (2010). Lessons on

financial planning for young

investors.

295 This was defined as “… shop around by comparing financial products from different organisations”. See, ACNeilson (2005). ANZ Survey of Adult

Financial Literacy in Australia. Australia.

Table 3.1 Continued

128

3.9.2 Description of variables used as investment alternatives

Table 3.2 shows the description of variables used as investment alternatives under this

study.

Table 3.2 Description of Variables Used as Investment Alternatives for this Study

Variable Operational Definition Source

Post Office

Saving

Schemes

Investments in Post office & other similar

Saving Schemes such as

POMIS/NSS/KVP/PPF/PF etc.

SEBI and NCAER

(2011)

Insurance and

Pension Plans

Insurance and pension plans of LIC and private

companies.

SEBI and NCAER

(2011)

Bank Deposits Fixed Deposits and Recurring Deposits with

commercial banks, Cooperative banks, Regional

Rural banks, financial institutions other than

above and Company Fixed Deposits

SEBI and NCAER

(2011)

Mutual Funds All the types of schemes provided by the mutual

fund companies.

SEBI and NCAER

(2011)

Shares Investment in types of shares through primary

market and/or secondary market

SEBI and NCAER

(2011)

Debentures All the type of debentures issued by companies. SEBI and NCAER

(2011)

Bonds Various types of bonds issued by Government

and Government Undertakings.

SEBI and NCAER

(2011)

Real Estate Real estate should not be used for

commercial/business purpose.

SEBI and NCAER

(2011)

Precious

Metals

Gold and Silver only (in any form) SEBI and NCAER

(2011)

129

3.9.3 Description of variables used as preferred source of information used under

study

Description of variables used as preferred source of information used under study is

presented in Table 3.3.

Table 3.3 Description of Variables used as Preferred Source of Information used

Under Study

Variables Scale used

to measure

variable

Type of

measurement used

to measure variable

Source

Certified

Financial

Planner

Interval Five Point Rating

Likert Scale

Sung and Sandager (1997),

Lin (2002)

Annual reports

of the company


Likert Scale

Lin (2002)

Prospectus of a

company


Likert Scale

Lin (2002)

Company‘s

website


Likert Scale

Nick et. al (2010), NCAER

and SEBI (2011)

Distributers/agen

ts of financial

product


Likert Scale

Lin (2002), NCAER and

SEBI (2011)

Rating agencies‘

reports


Likert Scale

Lin (2002), Lee and

Hogarth (2002b), Capon

and Lutz (1979)

Company‘s

telephone

representatives


Likert Scale

NCAER and SEBI (2011)

Family members Interval Five Point Rating

Likert Scale

Lin (2002), Nagy and

Obenberger (1994)

Friends and

relatives


Likert Scale


Lin (2002)

Conversation/ex

changes of views

with professional

colleagues


Likert Scale

Arnswald (2001), Nagy and

Obenberger (1994), Capon

and Lutz (1979), Lee and

Hogarth (2002b)

130

Variables Scale used

to measure

variable

Type of

measurement used

to measure variable

Source

Publication in

the financial

press and news

papers and

electronic media


Likert Scale

Arnswald (2001), NCAER

and SEBI (2011), Lin

(2002), Lee and Hogarth

(2002b),

Conversation/

exchanges of

views with

company

executive and

sector experts


Likert Scale

Arnswald (2001), Lin

(2002), Capon and Lutz


(2002b)

Corporate

forecast prepared

by independent

investment

company


Likert Scale

Arnswald (2001), Capon

and Lutz (1979), Lee and

Hogarth (2002b)

Published reports

from research

agencies


Likert Scale

Arnswald (2001), Lin

(2002), Capon and Lutz


(2002b)

Opinions from

existing

investors of

various

instruments


Likert Scale

Lin (2002)

Financial

advisors/Broker

and analyst‘s

recommendation


Likert Scale


Lin (2002), Krishnan and

Brooker (2002), Nagy and

Obenberger (1994)

Table 3.3 Continued

131

3.9.4 Description of variables influencing investment decision used under study

Description of variables used as influencing investment decision used under study is


Table 3.4 Description of Variables Influencing Investment Decision used Under

Study


measure

variable

Type of

measurement

used to measure

variable

Source

Condition of financial

statement


Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Expected Corporate Earning Interval Five Point Rating

Likert Scale

Nagy and

Obenberger (1994)

Past performance of the firm

(in terms of profit and return

given to investors)


Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Company‘ s position in the

industry


Likert Scale

Hussein, et al.

(2009)

Insiders‘ information Interval Five Point Rating

Likert Scale

Hussein, et al.

(2009)

The result of fundamental

analysis


Likert Scale

Chandra et al. (2011)

The result of technical

analysis


Likert Scale


Expected return on

investment


Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Feeling for a company‘s

products and services


Likert Scale

Hussein, et al.

(2009), Merikas et

al. (2003)

Perceived ethics of company Interval Five Point Rating

Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Political party affiliation Interval Five Point Rating

Likert Scale

Hussein, et al.

(2009)

132


measure

variable

Type of

measurement

used to measure

variable

Source

Contribution of a firm

towards social causes


Likert Scale

Blumberg et al.

(1997)

Coverage in the press Interval Five Point Rating

Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Recent price movements in a

firm‘ s stock/NAV


Likert Scale

Nagy and

Obenberger (1994)

Statements from politicians

and governmental officials


Likert Scale

Hussein, et al.

(2009)

Fluctuations/developments

in the indices of the major

market


Likert Scale

Hussein, et al.

(2009)

Current economic indicators Interval Five Point Rating

Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Reputation of a company in

domestic market


Likert Scale

Hussein, et al.

(2009)

Nagy and

Obenberger (1994),


Reputation of a parent

company or sister concern


Likert Scale

Nagy and

Obenberger (1994)

Environmental Record Interval Five Point Rating

Likert Scale

Nagy and

Obenberger (1994)

Market Capitalization of

company


Likert Scale


Conversation/exchanges of

views with professional

colleagues


Likert Scale

Arnswald (2001),

Nagy and

Obenberger (1994)

Publication in the financial

press, newspapers and

electronic media


Likert Scale

Arnswald (2001)

Conversation/ exchanges of

views with company

executive and sector experts


Likert Scale

Arnswald (2001)

Table 3.4 Continued

133


measure

variable

Type of

measurement

used to measure

variable

Source

Studying the portfolio

investments of other market

players


Likert Scale

Arnswald (2001)

Corporate forecast prepared

by independent investment

company


Likert Scale

Arnswald (2001)

Economic forecasts by

research institutions


Likert Scale

Arnswald (2001)

Study of Annual Reports Interval Five Point Rating

Likert Scale

Nagy and

Obenberger (1994)

Opinions from family

members


Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Opinions from friends and

relatives


Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Opinions from existing

investors


Likert Scale

Hussein, et al.

(2009)

Financial advisors/Broker

and analyst‟s

recommendation


Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Opinion of Credit Rating

agencies‟ analysis


Likert Scale

Arnswald (2001)

Diversification needs Interval Five Point Rating

Likert Scale

Hussein, et al.

(2009), Nagy and

Obenberger (1994)

Liquidity associated with

investment


Likert Scale

SEBI (2010)

Availing the benefit of

income tax deduction


Likert Scale

Nagy and

Obenberger (1994)

Risk-return trade off Interval Five Point Rating

Likert Scale

SEBI (2010)

Minimizing risk Interval Five Point Rating

Likert Scale

Hussein, et al.

(2009)

Table 3.4 Continued

134


measure

variable

Type of

measurement

used to measure

variable

Source

Ease of obtaining borrowed

fund


Likert Scale

Hussein, et al.

(2009)

Preferred investment time

horizon


Likert Scale

SEBI (2010)

Safety associated with

investment


Likert Scale

SEBI (2010)

Affordable minimum

investment amount


Likert Scale

Nagy and

Obenberger (1994)

Ease in Liquidity Interval Five Point Rating

Likert Scale

SEBI (2010)

Guaranteed return Interval Five Point Rating

Likert Scale

SEBI (2010)

For this study, the scope of the term ‗company‘ includes banks, insurance companies,

financial institutions, mutual fund asset management companies and non-banking

financial companies. An in-depth description of the same in given below.

Bank

As per section 5(c) of Banking Regulation Act, 1949 a ―Banking Company‖ means any

company which transacts the business of banking India.

As per section 5(b) of Banking Regulation Act, 1949, ―banking‖ means the accepting, for

the purpose of lending or investment, of deposits of money from the public, repayable on

demand or otherwise, and withdrawal by cheque, draft, order or otherwise. (Source:

Ministry of Finance, Government of India (1949). The Banking Regulation Act, 1949.

Part I: Preliminary. 10th March, 1949.New Delhi, India, p.2.)

Insurance company

Table 3.4 Continued

135

As per the section 2 (20) of Companies Act, 1956; ―Insurance Company‖ means a

company which carries on the business of insurance either solely or by in conjunction

with any other business or businesses. (Source: The Companies Act, 1956, p. 20)

As per section 7(a) ―Insurance Company‖ means any insurer being a company-

(a) which formed and registered under the Companies Act, 1956 (1 of 1956);

(b) in which the aggregate holding of equity shares by a foreign company, either by

itself or through its subsidiary companies or its nominees, do not exceed twenty-

six percent equity capital of such Indian insurance company;

(c) whose sole purpose is to carry on life insurance business or general insurance

business or re-insurance business.

The insurance company includes, Indian Insurance Company, Foreign Insurance

Company and Insurance Co-operative Society. (Source: Government of India (2002). The

Insurance Act, 1938 (As amended by Insurance (Amended Act, 2002). Part – I:

Preliminary. p. 2).

Investment Company

―Investment Company‖ means a company whose principle business is the acquisition of

shares, stock debentures or other securities. (Source: Government of India (2002).The

Insurance Act, 1938 (As amended by Insurance (Amended Act, 2002). Part – I:

Preliminary, p. 2).

Financial Institutions

Financial institutions are financial intermediaries that mobilize savings and facilitate the

allocation of funds in an efficient manner. Financial institutions are classified as banking

and non-banking financial institutions. Non-banking financial institutions are

Developmental Financial Companies, Non-banking Finance Companies, Housing

136

Finance Companies. The Financial Institutions also include term-finance institutions such

as, IDBI, ICICI, IFCI, SIDBI and IIBI. IDFC, NABARD, NHB, UTI, LIC, GIC are

specialized financial institutions (Source: Pathak, B. (2008). The Indian Financial

Systems: Markets, Instruments and Services (2nd

ed.). New Delhi: Pearson Education. p.

3.)

As per the section 4 (A) of Companies Act, 1956; each of the financial institutions shall

be regarded as company for the purpose of this act. Provided that no institution shall be

so specified unless it has been established or constituted by or under any Central Act.

Non-Banking Financial Company is a company registered under the Companies Act,

1956 (Source: The Companies Act, 1956, p. 20).

Mutual Fund Asset Management Company

As per section 2 (d) of SEBI (Mutual Funds) Regulations, 1996; ―asset management

company‖ means a company formed and registered under Companies Act, 1956 (1 of

1956) and approved as such as the Board under sub regulation (2) of regulations 21.

(Source: The Gazatte of India. Securities and Exchange Board of India (Mutual Funds)

Regulations, 1996, Part II- Section 3 Subsection (ii), Chapter 1 – Preliminary, p. 7.)

3.10 Coding of Variables

Codes assigned to each variable of preferred sources of information and variables

influencing investment decision of investors are shown in Table 3.5 and Table 3.6

respectively.

137

Table 3.5 Codes Assigned to Variables used as Preferred Source of Information

used Under Study

No. Variables Code

assigned

1 Certified Financial Planner IS1

2 Annual reports of the company IS2

3 Prospectus of a company IS3

4 Company‘s website IS4

5 Distributers/agents of financial product IS5

6 Rating agencies‘ reports IS6

7 Company‘s telephone representatives IS7

8 Family members IS8

9 Friends and relatives IS9

10 Conversation/exchanges of views with professional colleagues IS10

11 Publication in the financial press and news papers and electronic

media

IS11

12 Conversation/ exchanges of views with company executive and

sector experts

IS12

13 Corporate forecast prepared by independent investment company IS13

14 Published reports from research agencies IS14

15 Opinions from existing investors of various instruments IS15

16 Financial advisors/Broker and analyst‘s recommendation IS16

138

Table 3.6 Codes Assigned to Variables Influencing Investment Decision used Under

Study

No. Variables Code

assigned

1 Condition of financial statement ID1

2 Expected Corporate Earning ID2

3 Past performance of the firm (in terms of profit and return given to

investors)

ID3

4 Company‘ s position in the industry ID4

5 Insiders‘ information ID5

6 The result of fundamental analysis ID6

7 The result of technical analysis ID7

8 Expected return on investment ID8

9 Feeling for a company‘s products and services ID9

10 Perceived ethics of company ID10

11 Political party affiliation ID11

12 Contribution of a firm towards social causes ID12

13 Coverage in the press ID13

14 Recent price movements in a firm‘ s stock/NAV ID14

15 Statements from politicians and governmental officials ID15

16 Fluctuations/developments in the indices of the major market ID16

17 Current economic indicators ID17

18 Reputation of a company in domestic market ID18

19 Reputation of a parent company or sister concern ID19

20 Environmental Record ID20

21 Market Capitalization of company ID21

22 Conversation/exchanges of views with professional colleagues ID22

23 Publication in the financial press, newspapers and electronic

media

ID23

24 Conversation/ exchanges of views with company executive and

sector experts

ID24

25 Studying the portfolio investments of other market players ID25

26 Corporate forecast prepared by independent investment company ID26

27 Economic forecasts by research institutions ID27

28 Study of Annual Reports ID28

29 Opinions from family members ID29

30 Opinions from friends and relatives ID30

31 Opinions from existing investors ID31

32 Financial advisors/Broker and analyst‟s recommendation ID32

139

No. Variables Code

assigned

33 Opinion of Credit Rating agencies‟ analysis ID33

34 Diversification needs ID34

35 Liquidity associated with investment ID35

36 Availing the benefit of income tax deduction ID36

37 Risk-return trade off ID37

38 Minimizing risk ID38

39 Ease of obtaining borrowed fund ID39

40 Preferred investment time horizon ID40

41 Safety associated with investment ID41

42 Affordable minimum investment amount ID42

43 Ease in Liquidity ID43

44 Guaranteed return ID44

3.11 Data analysis

Raw data contained in the research instrument needs to be converted into suitable form so

that meaningful findings can be obtained. For this purpose, the data are to be coded and

transferred from research instrument to the designed format. Once, the data are

transferred properly, data analysis can be initiated. The data obtained against various

questions from 385 valid respondents were properly coded and transcribed into designed

format.

Analysis of data is the process by which data are converted into useful information.

Different data analysis techniques were used to get meaningful outcome from the data

obtained against different questions of the research instrument and transferred to the

format. Decisions as to which of the statistical techniques should be used were made on

the basis of the various criteria like (a) the scale and other characteristics of data, (b)

objectives of the study, (c) characteristics of the research design etc. Following

paragraphs provide a bird‘s eye view of data analysis techniques, which have been used

Table 3.6 Continued

140

for the overall analysis of this study. The detailing of these techniques has been done in

Chapter 4 at appropriate place for better understanding.

Various techniques of data analysis are available. Broadly, data analysis techniques are

divided into three categories296

.

1. Univariate, involving a single variable at a time,

2. Bivariate, involving two variables at a time and

3. Mutlivariate, involving three or more variables simultaneously.

3.11.1. Univariate techniques

Univariate techniques are appropriate when there is a single measurement of each

element in the sample or there are several measurements of each element but each

variable is analyzed in isolation. Univariate techniques can be classified based on

whether the data are metric or non-metric. Metric data are measured on an interval or

ratio scale. Non-metric data are measured on a nominal or ordinal scale.

Frequency distribution is most widely used in Univariate technique. For this study,

where one variable was to be considered at a time, frequency distribution was carried out,

to obtain a correct number of responses. Bar charts, pie charts, percentage etc. were used

for further analysis of such questions.

3.11.2 Bivariate techniques

Bivariabte techniques are appropriate when the researcher wants to analyze two variables

simultaneously. This technique is also used to find out the association between two

variables. Some Bivariate techniques like cross tabulation, chi-square tests, correlation

and regression analysis were used in the study.

296 Nargundkar R.(2004). Marketing Research- Text and Cases (2nd ed.). Tata McGraw Hill Publication,

120.

141

3.11.3 Multivariate techniques

Multivariate techniques are suitable for analyzing data when there are three or more

measurements of each element and where the variables are analyzed simultaneously.

Multivariate techniques are broadly classified as dependence techniques and

interdependence techniques.

Dependence techniques are used when one or more variables are designated as being

predicted by a number of independent (predictor) variables. For the present study binary

logistic regression analysis, as a dependency technique, was used to classify respondents

on the basis of their financial literacy level either as investor with lower financial literacy

or investor with higher financial literacy. Correlation and regression analysis were also

performed under this technique.

Interdependence techniques are concerned with the relationship of a set of variables in

which no one variable is designated as being predicted by other variables. For the present

study interdependence techniques like factor analysis and regression analysis were used.

3.11.4 Available Methodologies to Measure Financial Literacy

From the review of literature presented in the first chapter of this study, it is concluded

that there is diversity in conceptual definitions of the term ―financial literacy‖ and the

methods used to measure financial literacy under various study. On the basis of surveys

done across the various nations, it is found that there are two types of different

approaches used to measure financial literacy. One approach is to give respondents an

objective test (i.e. performance test) that measures their knowledge and understanding of

financial terms and ability to apply financial concepts to particular situations. These types

of surveys were conducted in the United States and Korea. The second approach is to ask

the respondents for self-assessment (i.e. self report methods), or for their perceptions, of

their financial understanding and knowledge, as well as their attitudes towards financial

142

instruments, decisions, information, and its receipts. This is the approach used by surveys

undertaken in the United Kingdom, Japan and Australia. From Table 3.7, it can be seen

that both the measurement methods have been employed by various researchers to

measure financial literacy in their studies.

Table 3.7 shows a particular methodology adopted by a variety of researchers, policy

makers and authorities to measure financial literacy across the several empirical studies

done in various countries. As mentioned above, both the measurement methods have

been employed to measure financial literacy. Performance tests are principally

knowledge based, reflecting conceptual framework and/or construction. Most of the

measurement of financial literacy has focused on the cognitive aspects of the concept and

what people know or understand about financial matters because ―to be financially

literate, individuals must demonstrate knowledge and skills needed to make choices

within a financial marketplace‖ (Huston 2010297

, p. 309–310). The performance test as a

method for measurement of financial literacy is most often conducted using a set of

multiple-choice test questions and/or true–false test questions that are included in a larger

survey instrument that asks about general or specific financial matters and behaviors

(e.g., Hilgert, Hogarth, and Beverly 2003298

; Lusardi and Mitchell 2007299

; Lusardi,

Mitchell, and Curto 2010300

).

In contrast, a self reported method assesses perceived knowledge or confidence in

knowledge (i.e. how much you think you know). The mismatch between self-assessed

financial knowledge and actual understanding of financial concepts may lead to the

overconfidence in the respondents/investors. A substantial academic literature in

cognitive psychology makes the case that people are usually overconfident and in

particular, they are overconfident about the precision of their knowledge (Odean,

297

Huston, S. J. (2010), Measuring Financial Literacy. Journal of Consumer Affairs, 44: 296–316. 298 Hilgert, M.A., Hogarth, J.M. & Beverly, S.G. (2003). Household financial management: The

connection between knowledge and behavior. Federal Reserve Bulletin, 89 (July): 309-322.Washinton,

D.C. 299 Lusardi, A. & Mitchell, O.S. (2007c).Financial Literacy and Retirement Planning: New Evidence from

the Rand American Life Panel. Michigan Retirement Research Center Working Paper 2007-157. 300 Lusardi, Annamaria, Olivia Mitchell, &Vilsa Curto (2010), ―Financial Literacy Among the

Young,‖ Journal of Consumer Affairs, 44(2), pp 358-380.

143

1998301

). Literature has also documented that in general; people tend to overestimate their

ability to do well at tasks, are unrealistically optimistic about future events and have

unrealistically positive self-evaluations. International financial literacy research studies

suggest that overconfidence regarding financial knowledge and understanding is a

significant issue that impacts upon both the degree to which people seek financial

information and advice, and the financial decisions that they subsequently make (Lusardi,

A. and O Mitchell, 2006302

). An OECD report (2005) discusses research across 12

countries that found that respondents felt they knew more about financial matters than

was actually the case (consumers often think that they know more than they actually do

(ACNielsen, 2005303

). This was particularly clear in research which combined objective

tests (that measured knowledge and understanding of financial terms and ability to apply

financial concepts to particular situations), with self-assessment (respondents‘

perceptions of their financial understanding and knowledge (OECD, 2005304

)). However,

it is a common finding that has been demonstrated not only in financial matters, but

across a wide range of knowledge and abilities (Alba & Hutchinson, 2000305

).

301 Odean, T. (1998). Volume, Volatility, Price and Profit when all Traders are Above Average, Graduate

School of Management, University of California -Davis, United States of America, draft April 1998. 302 Lusardi, A. & Mitchell, O. (2006). Financial Literacy and Retirement Preparedness: Evidence and

implications for financial education programs, Michigan Retirement Research Centre, Working paper

2006-144, November 2006, p. 8. 303 ACNielsen Research (2005). ANZ Survey of Adult Financial Literacy in Australia. Melbourne,

November 2005. 304

OECD, op. cit., pp. 43-44. In the 2005 ANZ survey of financial literacy, 67% of respondents said that

they understood the principle of compound interest, but only 28% were rated with a ‗good level‘ of

comprehension when they solved an actual problem. 305 Alba, J., & Hutchinson, J.W. (2000). Knowledge calibration: What consumers know and what they think

they know. Journal of Consumer Research, 27, 123-156.

144

Table 3.7 Methodology Adopted by Various Researchers for Measuring Financial

Literacy

Research studies

on measuring

financial literacy

Particulars Methodology adopted in

a research study

Self-

assessment

questions

Performance

Test

Volpe, Chen, &

Pavlicko (1996)306

Percent correct answers on 10

multiple-choice items

--- Yes

Chen & Volpe

(1998)307

Percent correct on 36 multiple-choice

items

--- Yes

Volpe, Kotel, &

Chen (2002)308

Correct responses on 10 multiple-

choice items

--- Yes

Hilgert, Hogarth, &

Beverley (2003)309

Percent correct on a knowledge test Yes Yes

FINRA (2003)310

Correct responses to 10 true/false

items

Yes Yes

Moore (2003)311

Financial knowledge: Number of

correct responses to 12 binary-choice

items.

Financial experiences: Report having

financial experiences across 14 items.

Financial behaviour: Report engaging

in positive and negative behaviours

across 15 items.

Debt confidence: Responding

―completely‖ or ―very confident‖

regarding debt considerations

Yes Yes

306

Volpe, R. P., Chen, H. & Pavlicko, J.J. (1996). Personal investment literacy among college students: A

survey. Financial Practice & Education, 6, 86-94. 307 Chen, H. & Volpe, R. P. (1998). Analysis of personal financial literacy among college students.

Financial Services Review, 7, 107-128. 308 Volpe, R.P., Kotel, J.E. & Chen H. (2002). A survey of investment literacy among online investors.

Financial Counseling and Planning, 13, 1-16. 309 Hilgert Hilgert, M.A., Hogarth, J.M. & Beverly, S.G. (2003) Household financial management: The

connection between knowledge and behavior. Federal Reserve Bulletin, 89 (July): 309-322.Washinton, D.C. 310 FINRA (2003). NASD investor literacy research: Executive summary. Accessed March 30, 2010 at

http://www.finrafoundation.org/surveyexecsum.pdf. 311

Moore, D. (2003). Survey of financial literacy in Washington State: Knowledge, behavior, Attitudes, and

Experiences. Technical Report # 03-39. Social and Economic Sciences Research Center, Washington State

Department of Financial Institutions, Olympia, WA . Puulman: Washington State University.


145

Research studies

on measuring

financial literacy


a research study

Self-

assessment

questions

Performance

Test

Mandell (2004)312

Percent correct on a 31-item

knowledge test

Yes

Agnew & Szykman

(2005)313

Number of correct responses to 10

multiple choice and true/false items.

Also, self-rated investment knowledge

relative to others on 1-10 scale.

Yes Yes

(NCEE) (2005)314

Percent correct on 24-item knowledge

test

--- Yes

Lusardi & Mitchell

(2006315

, 2008316

);

Correct responses to 3 multiple-choice

and true/false items

--- Yes

Lusardi & Mitchell

(2007a)317

Correct responses to 3 computational

items

Yes

Lusardi & Mitchell

(2007b)318

Single weighted average of

correct/incorrect responses (based on

factor analysis) of 5 multiple-choice

basic financial literacy items and 8

multiple choice sophisticated financial

literacy items. Separately considered a

7-pointitem on perceived knowledge.

--- Yes

312 Mandell, L. (2004). Financial Literacy: Are we improving? Jump$tart Coalition for Personal Financial

Literacy. 313 Agnew, J.R. & Szykman, L.R. (2005). Asset al.location and information overload: The influence of

information display, asset choice, and investor experience. Journal of Behavioral Finance, 6, 57-70. 314 National Council for Economic Education (NCEE) (2005), What American teens & adults know about

economics. Accessed March 30, 2010 at

http://www.ncee.net/cel/WhatAmericansKnowAboutEconomics_042605-3.pdf. 315 Lusardi, A., & Mitchell, O.S. (2006, October). Financial literacy and planning: Implications for

retirement wellbeing. Wharton School, University of Pennsylvania, Pension Research Council Working

Paper n. 1. 316 Lusardi, A., & Mitchell, O.S. (2008). Planning and financial literacy: How do women fare? American

Economic Review: Papers & Proceedings, 98, 413-417. 317 Lusardi, A., & Mitchell, O.S. (2007a). Baby boomer retirement security: The roles of planning, financial

literacy, and housing wealth. Journal of Monetary Economics, 54, 205-224. 318 Lusardi, A., & Mitchell, O.S. (2007b, October). Financial literacy and retirement planning: New

evidence from the RAND American Life Panel. MRRC Working Paper No. 2007-157.

Table 3.7 Continued

146

Research studies

on measuring

financial literacy


a research study

Self-

assessment

questions

Performance

Test

Mandell (2007)319

Percent correct on a knowledge test --- Yes

van Rooij, Lusardi,

& Alessie (2007)320

Two weighted averages of

correct/incorrect responses (based on

factor analyses) for (a) 5 multiple-

choice basic financial literacy items

and (b) 11 multiple-choice

sophisticated financial literacy items.

Separately considered a 7-point item

on perceived knowledge.

--- Yes

Lusardi & Tufano

(2008)321

Correct responses to 3 individual

multiple-choice items

Yes Yes

ANZ Bank

(2008)322

Mean score, based on target responses

to 26 questions derived from an

operational framework

Yes Yes

Hussein et al.

(2009)323

Percent of correct answers 18 exam

type questions

--- Yes

3.11.5 Methodology used to measure Financial Literacy for Present Study

On basis of above explanation regarding various methodologies available to measure

financial literacy and to overcome the limitation of overconfidence reflected in the self-

reported method of measuring financial literacy, the researcher has not used questions

based on self-assessment to measure financial literacy level. Therefore researcher has

319 Mandell, L. (2007). Financial literacy of high school students. In J.J. Xiao (Ed.), Handbook of Consumer

Finance Research (pp. 163-183). New York, NY: Springer. 320 van Rooij, M., Lusardi, A., & Alessie, R. (2007, October). Financial literacy and stock market

participation. Dartmouth College, MRRC Working Paper 2007-162. 321 Lusardi, A. & Tufano, P. (2008). Debt literacy, financial experiences, and overindebtedness. Dartmouth Working Paper. 322 ANZ Bank (2008). ANZ survey of adult financial literacy in Australia. Accessed March 30, 2010 at

http://www.anz.com/Documents/AU/Aboutanz/AN_5654_Adult_Fin_Lit_Report_08_Web_Report_full.pdf 323 Hussein A. H. Al- Tamini & Al Anood Bin Kali (2009). Financial literacy and investment decision of

UAE investors. The Journal of Risk Finance, 10 (5), Emerald Group Publishing limited, 508

Table 3.7 Continued

147

gone for the performance test. To measure the financial literacy of respondents,

investor/respondent‘s total score was calculated as the percentage of correct answers324

,

by attempting the total 50 questions. Out of these, basic financial literacy consisted of 20

questions and advanced financial literacy consisted of 30 questions. The median

percentage of correct answers of the sample was considered to frame financial literacy

level and/or to classify the subgroups. The respondents with scores above median are

considered as respondents with higher financial literacy and hence classified as higher

financially literate and respondents with equal and/or lower than median are considered

as respondents with relatively lower level of financial literacy and hence classified as

lower financially literate. The in-depth explanation of these categories is given in chapter

4.

To generate a score to measure financial literacy, each statement/questions in the

performance test has been assigned 1 mark. If a respondent gave a correct answer to a

question, he/she has been awarded one mark for that question. No mark was given for

incorrect answers, for refusing to answer questions, or for answers ―don‘t know‖.

In this survey, the respondents were instructed to answer the questions on the basis of

their own understanding on the subject. They were neither allowed to consult others for

additional information nor allowed to use calculator/similar device to answer the

questions.

324

Lyons, A., Rachlis, M., & Scherpf, E. (2007). What‘s in a Score? Differences in Consumers‘ Credit


WP-01, retrieved on January 21, 2012 from www.networksfinancialinstitute.org

148

3.12 Hypotheses of the study

1. Ho : There is no significant association between investors‘ demographic and

socio-economic variables and their financial literacy level.

H1 : There is a significant association between investors‘ demographic and

socio-economic variables and their financial literacy level.

1.1 Ho There is no significant association between investors‘ age and their

financial literacy level.

H1 There is a significant association between investors‘ age and their


1.2 Ho There is no significant association between investors‘ gender and their


H1 There is a significant association between investors‘ gender and their


1.3 Ho There is no significant association between investors‘ education and

their financial literacy level.

H1 There is a significant association between investors‘ education and their


1.4 Ho There is no significant association between investors‘ monthly income

and their financial literacy level.

H1 There is a significant association between investors‘ monthly income


1.5 Ho There is no significant association between investors‘ stage in family

life cycle and their financial literacy level.

H1 There is a significant association between investors‘ stage in family life

149

cycle and their financial literacy level.

1.6 Ho There is no significant association between investors‘ employment

structure and their financial literacy level.

H1 There is a significant association between investors‘ employment

structure and their financial literacy level.

1.7 Ho There is no significant association between investors‘ type of work

place activity and their financial literacy level.

H1 There is a significant association between investors‘ type of work place

activity and their financial literacy level.

1.8 Ho There is no significant association between investors‘ years of work

experience and their financial literacy level.

H1 There is a significant association between investors‘ years of work


1.9 Ho There is no significant association between investors‘ years of

investment experience and their financial literacy level.

H1 There is a significant association between investors‘ years of investment


1.10 Ho There is no significant association between number of times investors

shop around and their financial literacy level.

H1 There is a significant association between number of times investors

shop around and their financial literacy level.

1.11 Ho There is no significant association between investors‘ financial risk

tolerance and their financial literacy level.

H1 There is a significant association between investors‘ financial risk

tolerance and their financial literacy level.

150

2. Ho : There is no difference between preference for the selected informative

variables and their influence on investment decision under study.

H : There is a difference between preference for the selected informative


3. Ho : There is no significant impact of investors‘ demographic and socio-

economic variables on their financial literacy level.

H1 : There is a significant impact of investors‘ demographic and socio-

economic variables on their financial literacy level.

4. Ho : There is no significant association between the financial literacy level of

investors and their monthly expenditure to monthly income ratio.

H1 : There is a significant association between the financial literacy level of

investors and their monthly expenditure to monthly income ratio.

5. Ho : There is no significant association between the financial literacy level of

investors and their monthly saving to monthly income ratio.

H1 : There is a significant association between the financial literacy level of

investors and their monthly saving to monthly income ratio.

6. Ho : There is no significant impact of financial literacy level on investment


H1 : There is a significant impact of financial literacy level on investment


3.13 Conclusion

The present chapter has provided in-depth idea of research methodology adopted by the

researcher for this study. Later, data analysis begins with the preliminary check of all the

questionnaires for its completeness. Examination of filled up questionnaire was done to

detect the error, omission of half-filled and un-qualified questionnaires and to correct the

151

errors wherever possible, to ensure accuracy, consistency and uniformity of data. Then

numerical codes have been assigned to represent a specific response to a specific question.

After this, the data were tabulated, i.e. arranged in a logical manner in columns and rows

for further analysis. In-depth discussion on data analysis is presented in the next chapter.

Data Analysis and

Interpretation

Chapter 4

152

4.1 Introduction

4.2. Frequency distribution showing profile of study‟s respondents

4.3 Analysis of Financial Literacy Questions

4.4 Analysis of existing investment pattern of investors

4.5 Cross Tabulation

4.5.1 Cross Tabulation of ranks given by the respondents to investment

objectives

4.5.2 Cross Tabulation of ranks given for preferred Investment

Alternative

4.6 Preference given to the variables as a Source of Information

4.7 Preference towards selected sources of information and their influence on

investment decisions

4.7.1 Three most preferred variables as source of information

4.7.2 Three least preferred variables as source of information

4.7.3 Three most influencing informative factors on investment

Decision

4.7.4 Three most influencing informative factors on investment

Decision

4.7.5 Gap Analysis

4.7.6 Paired „t‟ test

4.8 Reliability and Normality of data

4.8.1 Reliability of Measurement

4.8.2 Data quality and normality check

4.9 Factor Analysis

4.9.1 Factor analysis for factors preferred by respondents as source of

Information

4.9.1.1 Bartlett‟s test of Sphericity

4.9.1.2 Kaiser-Meyer-Olkin Test for Sampling Adequacy

4.9.1.3 Anti-Image Correlation Matrix

153

4.9.1.4 Communalities

4.9.1.5 Variance explained

4.9.1.6 Factor Extraction

4.9.1.7 Factor Loading

4.9.1.8 Rotated Factor Matrix

4.9.1.9 Naming of the factors

4.9.1.10 Mean score of extracted factors

4.9.2 Factor analysis for variables influencing investment decision

4.9.2.1 Bartlett‟s test of sphericity


4.9.2.3 Measure of Sampling Adequacy




4.9.2.7 Naming of factors

4.9.2.8 Mean score of extracted factors influencing investment decision

4.10 Cross Tabulation and statistical tests

4.10.1 Association between investors‟ age and their financial literacy level

4.10.2 Association between investors‟ gender and their financial literacy

Level

4.10.3 Association between investors‟ education and their financial literacy

Level

4.10.4 Association between investors‟ monthly income and their financial

literacy level

4.10.5 Association between investors‟ stage in family life cycle and their


4.10.6 Association between investors‟ employment structure and their


4.10.7 Association between investors‟ type of workplace activity and their


4.10.8 Association between investors‟ years of work experience and their

154


4.10.9 Association between investors‟ years of investment experience and


4.10.10 Association between numbers of times investors shop around and


4.10.11 Association between risk tolerance level of investors and their


4.11 Regression analysis (Binary Logistic Regression)

4.12 Association between financial literacy level of investors and their monthly

expenditure to monthly income ratio.


saving to monthly income ratio.

4.14 Regression Analysis: Impact of financial literacy on investment decision

4.14.1 Regression analysis: Financial literacy level and Factor 1-

Personal Financial Need


Accounting, Business and Financial Information


Economic and Regulatory Environment

4.14.4 Regression analysis: Financial literacy level and Factor 4 –

Operational Feedback


Advocate Recommendation


Overall Group Performance


Credit Features


Personal Inclination


Monetary Expectation

155

4.14.10 Regression analysis: Financial literacy level and sum of

Investment Decision Factors

4.15 Conclusion

156

4.1 Introduction

The purpose of this chapter is to analyze the raw data and convert them into some useful

information. This chapter includes compilation of primary data that is collected through

fieldwork. Broad observations are made after analyzing the data. The data were analyzed

using Statistical Package for Social Sciences version 16.0 and MS-Excel. Different types

of statistical tests were performed depending on the variables under study. The inferences

and conclusion are drawn from the output of these tests are presented in this chapter.

4.2. Frequency distribution showing profile of study‟s respondents

The research instrument required each respondent to provide his/her demographic and

socio-economic data that includes gender, age, level of education attempted, stage of


experience, proportion of monthly expenditure to monthly income, proportion of monthly

saving to monthly income, number of times respondent shop around/make inquiry while

investing and years of investment experience.

Table 4.1 shows profile of the respondents of this study. Form the Table, it can be seen

that the sample has a gender distribution of approximately 79.2% male (n=305) and

20.8% female (n=80). The age distribution of sample respondents is heavily dominated

by age group 36 - 45 years as its weight is 24.93% (n=96), in comparison with

respondents fall under the age group between 18-25 years who represent 23.11% (n=89),

respondents belonging from the age group of 26-35 years who represent 19.74% (n=76),

respondent in age between 46 – 55 are 19.48% (n=75) and respondents belonging to age

group 56 years and above are 12.72% (n=49).

Table 4.1 also shows the highest level of education attempted by the respondents, where

31.70% are post graduates (n=122), 30.90% are graduates (n=119). 11.94% (n=46) and

11.68% (n=45) respondents have completed higher secondary education and secondary

157

education respectively. Respondents, who have completed diploma and primary

education are comprised of 7.53% (n=29) and 6.23% (n=24) respectively.

With respect to monthly income of respondents, from the Table 4.1, it can be seen that

the highest proportion of respondents i.e. 24.70% earn monthly income of less than Rs.

10,000 (n=95), Monthly income between Rs. 10,001-Rs. 15,000 was earned by 22.81%

respondents (n=85). About 21.60% respondents and 20.30% respondents earn monthly

income between Rs. 15,001-Rs. 20,000 (n=83) and Rs. 20,001-Rs. 25,000 (n=78)

respectively. Only 11.40 % respondents earn monthly income more than Rs. 25,000

(n=44).

It is evident from Table 4.1 that sample is divided in the various stages of family life

cycle. Out of total sample size (n=385), 26.23% respondents are in the stage of middle

age married with dependent children (n=101), 24.67% respondents are younger married

with children (n=95), 17.40% respondents are young single (n=67). The respondents who

are young married without children are 17.40% (n=67) and the respondents who are

middle age married without dependent children are 8.57% (n=33) and the rest of the

respondents i.e. 5.71 % respondents are older married (n=22).

The distribution of sample respondents on the basis of employment structure is heavily

dominated by full time salaried group as its weight is 59.22 % (n=228) in comparison

with respondents of self employed who represent 17.14% (n=67), respondents belonging

to part time salaried group represent 10.90% (n=42), respondents in category of retired

are 5.19% (n=20), respondents belonging to casual are of 2.59% (n=10), housewives

represent 3.63% (n=14) and respondents of in the category of unemployed and others are

0.51% (n=2) and 0.51% (n=2) respectively. Sample distribution with regard to years of

work experience 18.44% respondents possess work experience of less than one year

(n=71), 16.36% (n=63) and 20.00% (n=77) of the total respondents possess work

experience between 6 to 10 years and 11 to 20 years respectively. The 29.35% (n=113)

and 15.85% (n=61) respondents possess the total work experience of 21 to 30 years and

more than 30 years respectively. With respect to type of workplace activity, the

158

respondents working in finance related industry (i.e. Bank, Chartered Accountant,

Certified Financial Planner, Mutual Fund, Insurance Company, Investment Company

and/or any other financial institution) represent 34.50% (n=133), whereas respondents not

working in finance related industry (other than mentioned above) represent 62.90%

(n=242), while other respondents represent 2.60% (n=10).

Table 4.1 also shows the number of times respondents shop around/make inquiry while

investing his/her saving. Out of total respondents, 39.22 % shop around in between 1-3

times (n=151), 28.83% respondents shop around in between 4-6 times (n=111). 22.60%

(n=87) do not shop around/make inquiry at all while investing and 9.35% (n=36)

respondents shop around/make inquiry more than 6 times. The distribution of sample

according to number of years of investment experience is constituted by 34.55%

respondents who have been investing for 1-5 years (n=133) of the total sample, 27.01%

respondents who have been investing for 6-10 years (n=104), while 20.26% (n=78) and

18.18% (n=70) respondents have been investing for more than 10 years and less than 1

year respectively.

With regard to monthly expenditure to monthly income ratio of respondents, from Table

4.1, it can be seen that the highest proportion i.e. 32.73% (n=126) respondents‘ monthly

expenditure to monthly income ratios was between 1% to 50%. In the same way 23.11%

(n=89) and 21.56% (n=83) of total respondents‘ monthly expenditure to monthly income

ratio was 51% to 60% and 61% to 70% respectively. While 13.51% (n=52) and 7.79%

(n=30) respondents‘ monthly expenditure to monthly income ratio was 71% to 80% and

81% to 90% respectively. The 1.30% (n=5) respondents‘ monthly expenditure to monthly

income ratio was more than 90%.

Similarly, for monthly saving to monthly income ratio of respondents, from Table 4.1, it

can be seen that the highest proportion i.e. 56.37 % (n=217) of respondents‘ monthly

saving to monthly income ratios was 1% to 50%. In the same way, 32.99% (n=127) and

10.39% (n=40) respondents‘ monthly saving to monthly income ratio was 51% to 60%

and 61% to 70% respectively. Only 0.26% (n=1) respondents‘ monthly saving to monthly

159

income ratio was 71% to 80%. None of the respondent‘s monthly saving to monthly

income ratio was more than 81%.

With regard to risk tolerance level of respondents, 6.20% are lowest risk takers (n=24),

17.90% are moderate risk takers (n=69), 36.40% are high risk takers (n=140) and 39.50%

are highest risk takers (n=152).

Table 4.1 Respondents‟ Profile

Variables Categories Frequency Percentage

(in %)

Gender Male 305 79.23

Female 80 20.77

Age Group 18 to 25 years 89 23.11

26 to 35 years 76 19.74

36 to 45 years 96 24.93

46 to 55 years 75 19.48

56 to 65 years 49 12.72

66 years and above 0 0.00

Education Primary 24 6.23

Secondary 45 11.68

Higher secondary 46 11.94

Diploma 29 7.53

Graduation 119 30.90

Post-graduation 122 31.70

Monthly Income

(in Rs.)

Rs. 10,000 and less 95 24.70

Rs. 10,001 to Rs. 15,000 85 22.10

Rs. 15,001 to Rs. 20,000 83 21.60

Rs. 20,001 to Rs. 25,000 78 20.30

Rs. 25,001 and above 44 11.40

Stage in family life

cycle

Young single 67 17.40

Young married without children 67 17.40

Young married with children 95 24.67

Middle age married with children 101 26.23

Middle age married without

dependent children 33 8.57

Older married 22 5.71

Older unmarried 0 0.00

160


(in %)

Employment

Structure

Full time salaried 228 59.22

Part time salaried 42 10.90

Casual 10 2.59

Self Employed 67 17.14

Housewife 14 3.63

Retired 20 5.19

Unemployed 2 0.51

Others 2 0.51

Type of workplace

activity

Finance related work activity 133 34.50

Non finance related work activity 242 62.90

Other 10 2.60

Years of work

experience

Less than five 71 18.44

6 Years to 10 years 63 16.36

11 years to 20 years 77 20.00

21 years to 30 years 113 29.35

More than 30 years 61 15.85

Number of times

shop around/make

inquiry while

investing

Zero 87 22.60

1 to 3 151 39.22

4 to 6 111 28.83

More than 6 36 9.35

Years of Investment

Experience

Less than 1 70 18.18

1 to 5 Years 133 34.55

5 to 10 Years 104 27.01

More than 10 Years 78 20.26

Monthly

expenditure to

monthly income

ratio

1 % to 50 % 126 32.73

51 % to 60 % 89 23.11

61 % to 70 % 83 21.56

71 % to 80 % 52 13.51

81 % to 90 % 30 7.79

More than 90 % 5 1.30

Monthly

expenditure to

monthly income

ratio

1 % to 50 % 217 56.37

51 % to 60 % 127 32.99

61 % to 70 % 40 10.39

71 % to 80 % 1 0.26

81 % to 90 % 0 0.00

More than 90 % 0 0.00

Table 4.1 Continued

161


(in %)

Risk tolerance level Lowest risk takers 24 6.20

Moderate risk takers 69 17.90

High risk takers 140 36.40

Highest risk takers 152 39.50

4.3 Analysis of Financial Literacy Questions

The in-depth explanation for methodology used to measure the financial literacy level of

respondents for present study is given in Chapter 3. Following this, to measure the

financial literacy of respondents, investor/respondent‘s total score was calculated as the

percentage of correct answers (Lyons, 2007325

), by attempting the total 50 questions. Out

of these, basic financial literacy consisted of 20 questions and advanced financial literacy

consisted of 30 questions. The median percentage of correct answers of the sample was

considered to frame financial literacy level and/or to classify the subgroups. The

respondents with scores above median are considered as respondents with higher

financial literacy and hence classified as higher financially literate and respondents with

equal and/or below median are considered as respondents with relatively lower level of

financial literacy and hence classified as lower financially literate.

Table 4.2 shows the values of mean and median percentage of correct scores for the

entire survey, calculated on the basis of survey responses collected from the each investor

(respondent). The result shows that on an average, respondent answered 56.90 per cent of

the questions correctly. The median percentage of correct scores is 56.00. As explained in

the Chapter 3, this median percentage of correct scores of the sample was considered to

frame financial literacy level and/or to classify the respondents in to different subgroups.

The respondents with scores above median (i.e. 56 per cent) are considered as

respondents (investors) with higher financial literacy and hence classified in the first

325

Lyons, A., Rachlis, M., & Scherpf, E. (2007). What‘s in a Score? Differences in Consumers‘ Credit


WP-01, retrieved on January 21, 2012 from www.networksfinancialinstitute.org

Table 4.1 Continued

162

category, i.e. investors with relatively higher level of financial literacy and respondents

with equal to and lower than median (i.e. 56 per cent) are considered as respondents with

relatively lower level of financial literacy and hence classified into second category, i.e.

investors with relatively lower level of financial literacy

Table 4.2 Overall Financial Literacy of Respondents

Central tendency Value

Mean 56.90

Median 56.00

Mode 56

Std. Deviation 14.258

Minimum 20

Maximum 98

The overall performance of the respondents towards 20 questions of basic financial

literacy is presented in Table 4.3. The second column of the same table represents the

percentage of total respondents who answered each question correctly. On the basis of

percentage of correct answers to each question, sorting was done and the rank was

assigned. From Table 4.3, it can be seen that the respondents earned highest score on the

question of numeracy, suggesting that investors know this concept very well. Nine other

subject questions had scores higher than the median. In the ascending order (on the basis

of ranks assign) these subjects are consumer rights and responsibility, concept of know

your customer (KYC), interest compounding, functioning of stock market, relationship

between investment time horizon and fluctuation in asset value, diversification, inflation,

risk-return trade off and risk-return trade off of two assets. On the other hand, the subject

questions on which the respondents scored less than the median are concept of

investment, financial worth, risk, relationship between investment time horizon and asset

growth, personal finance, time value of money, relationship between interest and asset

prices, regulatory as a part of market structure, concept of asset allocation and disposable

income.

163

Table 4.3 Summary of Answers given by the Respondents under Basic Financial Literacy Test

Basic Financial Literacy Subject Question No. of

Respondents

given

Correct/True

Answers

Percentage of

Respondents

given

Correct/True

Answers

No. of

Respondents

given False

Answers

Percentage

of

Respondents

given False

Answers

No. of

Respondents

given answer

of Don‟t

know

Percentage of

Respondents

given answer

of Don‟t

know

Rank

Investment concept 200 51.95 172 44.67 13 3.38 11

Financial worth 193 50.13 154 40.00 38 9.87 12

Disposable income 87 22.60 213 55.32 85 22.08 20

Personal finance 162 42.08 160 41.56 63 16.36 15

Numeracy 311 80.78 59 15.32 15 3.90 1

Interest compounding 295 76.62 66 17.14 24 6.23 4

Inflation 265 68.83 82 21.30 37 9.61 8

Time value of money 160 41.56 176 45.71 49 12.73 16

Functioning of stock market 282 73.25 80 20.78 23 5.97 5

Concept of diversification 266 69.09 96 24.94 23 5.97 7

Risk-return trade off 253 65.71 93 24.16 39 10.13 9

Risk 186 48.31 180 46.75 19 4.94 13

Risk-return trade off of two assets 251 65.19 91 23.64 43 11.17 10

Relationship between investment time

horizon and asset growth 181 47.01 166 43.12 38 9.87 14

Investment time horizon and fluctuation in

asset value 275 71.43 86 22.34 24 6.23 6

concept of asset allocation 106 27.53 208 54.03 71 18.44 19

Relationship between interest and asset

prices 159 41.30 191 49.61 35 9.09 17

Consumer rights and responsibility 309 80.26 60 15.58 16 4.16 2

Regulatory body as a part of market structure 107 27.79 192 49.87 86 22.34 18

Concept of KYC 304 78.96 39 10.13 42 10.91 3

164

Table 4.4 shows overall performance of the respondents towards 30 questions of

advanced financial literacy. With regard to advanced financial literacy, as can be seen

from Table 4.4, respondents scored highest score on the product i.e. fixed deposits (

74.89% of correct answers), followed by insurance plans (62.86% of correct answers),

mutual funds (60.69% of correct answers), national savings certificates (60.00% of

correct answers), preference shares (56.23% of correct answers). The respondents are less

knowledgeable on the investment alternatives, i.e. equity shares (54.81% of correct

answers), employee provident fund (51.00% of correct answers), Post office monthly

income schemes (50.22% of correct answers), public provident fund (49.87% of correct

answers) and Debentures and Bonds (48.74% of correct answers), which is far from

median score. And hence it can be concluded that respondents are less financially

literate/knowledgeable on these investment alternatives.

165

Table 4.4 Summary of Answers given by the Respondents under Advanced Financial Literacy Test

Advanced financial literacy

question subject

No. of

correct/

true

answers

No. of

correct/

true

answers

No. of false

answers

Percentage

of false

answers

No. of Don‟t

know

answers

Percentage

of Don‟t

know

answers

Rank

Fixed deposits 865 74.89 201 17.40 89 7.71 1

National saving certificates 693 60.00 256 22.16 206 17.84 4

Public provident fund 576 49.87 357 30.91 222 19.22 9

Employee provident fund 589 51.00 424 36.71 142 12.29 7

Equity shares 633 54.81 407 35.24 115 9.96 6

Preference shares 433 56.23 203 26.36 134 17.40 5

Mutual funds 701 60.69 235 20.35 219 18.96 3

Debentures and Bonds 563 48.74 378 32.73 214 18.53 10

Post office monthly income

schemes 580 50.22 362 31.34 213 18.44

8

Insurance plans 968 62.86 394 25.58 178 11.56 2

166

The overall results shows that out of 385 respondents 40.78% respondents (n=157)

scored higher than the median, which is 56.00, and hence these respondents are

considered as investors with higher level of financial literacy. The rest of the 59.22% of

respondents (n=228) have scored equal and/or lower than median. These investors are

considered as respondents with relatively lower level of financial literacy and hence

classified as lower financially literate. Fig. 4.1 shows the classification of respondents on

the basis of their financial literacy level.

Fig. 4.1 Pie chart of classification of respondents

4.4 Analysis of existing investment pattern of investors

Table 4.5 shows the investment alternatives in which the investors have invested their

savings. From the same table, it can be seen that out of 385 total respondents, 318

respondents have invested in bank deposits, followed by insurance and pension plans.

The 279 respondents have invested in precious metals (gold and silver), while 157

respondents have invested in mutual funds.148, 134 and 122 respondents have invested in

shares, post office saving schemes and real estate respectively. While only 33 investors

have invested in bonds and debentures.

59%

41%

Low High

167

Table 4.5 Existing Investment Pattern of Investors

Investment Alternative Male Female Total

Post Office Saving Schemes 102 32 134

Insurance and pension plans 243 56 299

Bank deposits 247 71 318

Mutual funds 135 22 157

Shares 132 16 148

Debentures and Bonds 26 06 033

Real Estate 104 18 122

Precious metals (Gold and silver) 217 62 279

4.5 Cross Tabulation

In this section, simultaneous analysis of two variables is carried out through cross-

tabulation.

4.5.1 Cross tabulation of ranks given by the respondents to investment objectives

The respondents were asked to give ranks to given investment objectives. The rankings

given by the respondents are presented in Table 4.6. Table 4.6 presents the cross

tabulation of ranks given by the respondents to the given investment objectives. From the

same table, it can be seen that 35.32% (n=136) of the total respondents have given the

first rank to saving of income tax as an investment objective, while only 4.16% (n=16)

have given the seventh rank to the same investment objective. The Table 4.6 also shows

that 72.99% (n=281) respondents have given the seventh rank to

gift/donation/vacation/pilgrim as an investment objective, 21.82% (n=84) respondents

have given second rank to child‘s marriage/child‘s education/social ceremony. The

12.21% (n= 47) respondents have given first rank to secured retirement and safeguarding

against inflation/capital appreciation. With regard to buying/improving home and

meeting unexpected financial needs, only 9.87% (n= 38) and 14.55% (n=56) respondents

168

have given first rank respectively. The graphical representation of this data in percentage

value is given in Fig. 4.2.

Table 4.6 Cross Tabulation of Ranks given to Investment Objectives

Investment

Objectives

Rank

1 2 3 4 5 6 7

Saving income tax 136

(35.32)

33

(8.57)

36

(9.35)

57

(14.81)

54

(14.03)

53

(13.77)

16

(4.16)

Child‘s marriage/

child‘s education/

social ceremony

50

(12.99)

84

(21.82)

68

(17.66)

58

(15.06)

44

(11.43)

66

(17.14)

15

(3.90)

Buying/improving

home

38

(9.87)

38

(9.87)

38

(9.87)

46

(11.95)

98

(25.45)

105

(27.27)

22

(5.71)

Secured

retirement

47

(12.21)

85

(22.08)

80

(20.78)

79

(20.52)

51

(13.25)

30

(7.79)

13

(3.38)

Gift/donation/vaca

tion/

Pilgrim

4

(1.04)

6

(1.56)

13

(3.38)

8

(2.08)

19

(4.94)

54

(14.03)

281

(72.99)

Meeting

unexpected

financial needs

56

(14.55)

80

(20.78)

86

(22.34)

85

(22.08)

50

(12.99)

20

(5.19)

8

(2.08)

Safeguard against

inflation/ capital

appreciation

47

(12.21)

58

(15.06)

73

(18.96)

55

(14.29)

66

(17.14)

57

(14.81)

29

(7.53)

Note: Figures in parenthesis shows the percentage of respondents

169

Fig. 4.2 Bar chart of ranks given by the respondents to investment Objectives (in per cent)

35.32

12.99

9.87

12.21

1.04

14.55

12.21

8.57

21.82

9.87

22.08

1.56

20.78

15.06

9.35

17.66

9.87

20.78

3.38

22.34

18.96

14.81

15.06

11.95

20.52

2.08

22.08

14.29

14.03

11.43

25.45

13.25

4.94

12.99

17.14

13.77

17.14

27.27

7.79

14.03

5.19

14.81

4.16

3.90

5.71

3.38

72.99

2.08

7.53

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Saving income tax

Child’s marriage/child’s education/social ceremony

Buying/improving home

Secured retirement

Gift/donation/vacation/pilgrim

Meeting unexpected financial needs

Safeguard against inflation/ capital appreciation

Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 Rank 6 Rank 7

35.32

12.99

9.87

12.21

1.04

14.55

12.21

8.57

21.82

9.87

22.08

1.56

20.78

15.06

9.35

17.66

9.87

20.78

3.38

22.34

18.96

14.81

15.06

11.95

20.52

2.08

22.08

14.29

14.03

11.43

25.45

13.25

4.94

12.99

17.14

13.77

17.14

27.27

7.79

14.03

5.19

14.81

4.16

3.90

5.71

3.38

72.99

2.08

7.53

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Saving income tax

Child’s marriage/child’s education/social ceremony


Secured retirement

Gift/donation/vacation/pilgrim



Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 Rank 6 Rank 7

170

Total score of each investment objective is calculated on the basis of ranks given by the

respondents to each investment objective. Seven points are given to the first rank, six

points are given to the second rank and in the same way, one point is given to the seventh

rank. Based on these points, mean scores are calculated by adding the rank points and

divided by the total number of respondents. These mean scores of investment objectives

are presented in Table 4.7 and Fig. 4.3. From Table 4.7, it is found that saving of income

tax and meeting unexpected financial needs have the highest mean score i.e. 4.78,

followed by investment objective secured retirement having a mean score of 4.63. Other

investment objectives as per the descending order on mean score are Child‘s marriage/

child‘s education/social ceremony, Safeguard against inflation/capital appreciation,

Buying/improving home and Gift/ donation/ vacation/ vacation/ pilgrim.

Table 4.7 Mean Score of Investment Objectives

Investment Objective Mean score

Saving income tax 4.78

Child‘s marriage/ child‘s education/social ceremony 4.43

Buying/improving home 3.62

Secured retirement 4.63

Gift/ donation/ vacation/ pilgrim 1.58

Meeting unexpected financial needs 4.78

Safeguard against inflation/ capital appreciation 4.16

Fig. 4.3 Bar chart of mean score of investment objectives

4.78

4.43

3.62

4.63

1.58

4.78

4.16

0 1 2 3 4 5 6

Saving income tax

Child’s marriage/ child’s education/social ceremony


Secured retirement

Gift/ donation/ vacation/ pilgrim



Mean score

171

4.5.2 Cross Tabulation of ranks given for preferred Investment Alternative

Table 4.8 shows the cross tabulation of ranks given by the respondents to the various

investment alternatives according to their preference. From Table 4.8, it can be seen that

bank deposits are the most preferred investment alternative, as 38.96% (n=150)

respondents have given it the first rank. The second and third most preferred investment

alternatives are precious metals (gold and silver) and insurance and pension plans 15.32%

(n=59) and 14.03% (n=54) respondents have given them the first ranks accordingly.

From Table 5.8, it can be also seen that only 2.60% (n=10) respondents have given first

rank to bonds and debentures. The graphical representation of the same is done in Fig.

4.4.

Table 4.8 Cross Tabulation of Rank given for Preferred Investment Alternative

Investment

Alternatives

Rank

1 2 3 4 5 6 7 8

Post office

saving schemes

(POMIS/NSC/

KVP/PPF etc.)

41

(10.65)

75

(19.48)

31

(8.05)

42

(10.91)

44

(11.43)

30

(7.79)

53

(13.77)

69

(17.92)

Insurance and

pension

Plans

54

(14.03)

59

(15.32)

107

(27.79)

88

(22.86)

41

(10.65)

25

(6.49)

7

(1.82)

4

(1.04)

Bank Deposits 150

(38.96)

53

(13.77)

50

(12.99)

23

(5.97)

23

(5.97)

50

(12.99)

27

(7.01)

9

(2.34)

Mutual funds 16

(4.16)

30

(7.79)

30

(7.79)

59

(15.32)

95

(24.68)

81

(21.04)

61

(15.84)

13

(3.38)

Shares 23

(5.97)

36

(9.35)

26

(6.75)

33

(8.57)

43

(11.17)

68

(17.66)

72

(18.7)

84

(21.82)

Debentures and

bonds

10

(2.60)

7

(1.82)

21

(5.45)

16

(4.16)

43

(11.17)

61

(15.84)

83

(21.56)

145

(37.66)

Real Estate 40

(10.39)

33

(8.57)

31

(8.05)

49

(12.73)

60

(15.58)

55

(14.29)

74

(19.22)

43

(11.17)

Precious metal

(Gold Silver)

59

(15.32)

94

(24.42)

84

(21.82)

73

(18.96)

40

(10.39)

12

(3.12)

8

(2.078)

15

(3.90) Note: Figures in parenthesis shows the percentage of respondents

172

Fig. 4.4 Bar chart for ranks given by the respondents to investment alternatives

10.65

14.03

38.96

4.16

5.97

2.60

10.39

15.32

19.48

15.32

13.77

7.79

9.35

1.82

8.57

24.42

8.05

27.79

12.99

7.79

6.75

5.45

8.05

21.82

10.91

22.86

5.97

15.32

8.57

4.16

12.73

18.96

11.43

10.65

5.97

24.68

11.17

11.17

15.58

10.39

7.79

6.49

12.99

21.04

17.66

15.84

14.29

3.12

13.77

1.82

7.01

15.84

18.70

21.56

19.22

2.08

17.92

1.04

2.34

3.38

21.82

37.66

11.17

3.90

0.00 20.00 40.00 60.00 80.00 100.00 120.00

Post

Insurance

Bank Deposits

MF

Shares

Debentures

Real Estate

Gold Silver

Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 Rank 6 Rank 7 Rank 8

173

Total score of each investment alternative is calculated on the basis of ranks given by the

respondents on the basis of their preference to each investment alternative. Eight points

are given to the first rank, seven points are given to the second rank and in the same way,

and one point is given to the eighth rank. Based on these points, mean scores are

calculated by adding the rank points and divided by the total number of respondents.

These mean score of each investment alternative on the basis of their preference are

presented in Table 4.9 and Fig. 4.5. From Table 4.9, it is found that bank deposits have

the highest mean score i.e. 5.96, followed by the precious metal (gold and silver) having

mean score 5.78. Other investment alternatives as per the descending order in mean score

are insurance/pension plans, Post office saving schemes (POMIS/NSC/KVP/PPF etc.),

Mutual funds, Real estates, Shares and Debentures and bonds.

Table 4.9 Mean Score of Each Investment Alternatives on the basis of Ranks given

by the Respondents According to their Preference

Investment Alternatives Mean score

Post office saving schemes

(POMIS/NSC/KVP/PPF etc.)

4.38

Insurance and pension plans 5.66

Bank Deposits 5.96

Mutual funds 4.09

Shares 3.54

Debentures and bonds 2.57

Real Estate 4.09

Precious metals (Gold and Silver) 5.78

174

Fig. 4.5 Bar chart of mean score of each investment alternatives on the basis of

ranks given by the respondents according to their preference

4.6 Preference given to the variables as a preferred source of information

There are various sources of information, from where investors gather the information.

For this study, 16 variables were identified as a source of information and the preference

of investors towards these informative variables were measured as per the data given in

Table 4.10 and Fig. 4.6. Both the number of respondents and percentage of respondents

are shown in the Table 4.10. Five point Likert scale (1= Not at all preferred, 2 = Least

preferred, 3 = Neutral, 4 = Preferred and 5 = The most preferred) was used to identify the

preference of investors towards these 16 variables as a source of information. From Table

4.10, it is observed that majority of the respondents preferred all the variables as source

to collect information under study.

4.38

5.66

5.96

4.09

3.54

2.57

4.09

5.78

0 2 4 6 8

Post office saving schemes …

Insurance and pension plans

Bank Deposits

Mutual funds

Shares

Debentures and bonds

Real Estate

Precious metals (Gold and Silver)

Mean score

175

Table 4.10 Preference given by the Respondents towards Variables as Preferred

Source of Information

Variables Not

Preferred

Least

Preferred

Neutral Preferred Most

Preferred

N % N % N % N % N %

Certified Financial

Planner

0 0 12 4.21 39 10.13 195 50.65 139 36.10

Annual reports of the

company

9 2.34 22 7.72 112 29.09 181 47.01 61 15.84

Prospectus of a

company

23 5.97 59 20.70 105 27.27 134 34.81 64 16.62

Company‘s website 3 0.78 30 10.53 124 32.21 194 50.39 34 8.83

Distributers/agents of

financial product

0 0 0 0.00 103 26.75 207 53.77 75 19.48

Rating agencies‘ reports 0 0 39 13.68 133 34.55 168 43.64 45 11.69

Company‘s telephone

representatives

0 0 9 3.16 192 49.87 172 44.68 12 3.12

Family members 0 0 8 2.81 151 39.22 144 37.40 82 21.30

Friends and relatives 5 1.30 29 10.18 83 21.56 190 49.35 78 20.26

Conversation/exchanges

of views with

professional colleagues

0 0 15 5.26 88 22.86 217 56.36 65 16.88

Publication in the

financial press and news

papers

0 0 30 10.53 132 34.29 176 45.71 47 12.21

Conversation/

exchanges of views with

company executive and

sector experts

0 0 21 7.37 51 13.25 229 59.48 84 21.82

Corporate forecast

prepared by independent

investment company

12 3.12 88 30.88 126 32.73 188 48.83 31 8.05

Published reports from

research agencies

18 4.68 40 14.04 117 30.39 156 40.52 54 14.03

Opinions from existing

investors of various

instruments

0 0 6 2.11 51 13.25 230 59.74 98 25.45

Financial

advisors/Broker and

analyst‘s

recommendation

0 0 9 3.16 94 24.42 208 54.03 74 19.22

176

Fig. 4.6 Bar chart of preference given by respondents towards factors as preferred source of information

0

2.34

5.97

0.78

0

0

0

0

1.30

0

0

0

3.12

4.68

0

0

4.21

7.72

20.70

10.53

0.00

13.68

3.16

2.81

10.18

5.26

10.53

7.37

30.88

14.04

2.11

3.16

10.13

29.09

27.27

32.21

26.75

34.55

49.87

39.22

21.56

22.86

34.29

13.25

32.73

30.39

13.25

24.42

50.65

47.01

34.81

50.39

53.77

43.64

44.68

37.40

49.35

56.36

45.71

59.48

48.83

40.52

59.74

54.03

36.10

15.84

16.62

8.83

19.48

11.69

3.12

21.30

20.26

16.88

12.21

21.82

8.05

14.03

25.45

19.22

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Certified Financial Planner

Annual reports of the company

Prospectus of a company

Company’s website

Distributers/agents of financial product

Rating agencies’ reports

Company’s telephone representatives

Family members

Friends and relatives

Conversation/exchanges of views with professional colleagues

Publication in the financial press and news papers

Conversation/ exchanges of views with company executive …

Corporate forecast prepared by independent investment …

Published reports from research agencies

Opinions from existing investors of various instruments

Financial advisors/Broker and analyst’s recommendation

Not Preferred Least Preferred Neutral Preferred Most preferred

177

4.7 Preference towards selected sources of information and their influence on

investment decisions

Table 4.11 Preference towards Selected Sources of Information and their Influence

on Investment Decisions

Variables Preference

(Mean score)

Influence

(Mean

score)

Gap

(Preference-

Influence)

Family members 3.78 3.58 0.20

Friends and relatives 3.80 3.73 0.07

Annual reports 3.68 4.09 -0.41

Conversation with Professional

Colleagues

3.86 2.94 0.92

Financial Press and Newspapers 3.62 2.97 0.65

Conversation /exchanges of views with

company executives and sector experts

3.98 3.97 0.01

Corporate forecast prepared by

independent investment company

3.51 2.48 1.03

Present investors 4.09 2.88 1.21

Advisor/brokers/analyst 3.90 3.67 0.23

Rating agencies‘ reports 3.57 4.17 -0.60

The mean score of each variable is calculated, which is based on the number assigned to

the different response category. For preference towards the variables, points are assigned

on a 1 to 5 Likert scale with point 1 representing ‗not at all preferred‘ and point 5

representing ‗the most preferred‘ are given to the respondents. Similarly, for influence of

factors, points are assigned on a 1 to 5 Likert scale with point 1 representing ‗the least

influence‘ and point 5 representing ‗the most significantly influence‘. The mean score of

each variable ranges from 0 to 5. The mean values obtained for each response category is


4.7.1 Three most preferred variables as source of information

Mean score of each variable is as given in Table 4.11. The response given by the

respondents to the variables represents their preference towards a particular source of

178

information. From Table 4.11, it can be seen that three most important variables (sources

of information) from the investors‘ point of view, are present investors, conversation

/exchanges of views with company executives & sector experts and

advisors/brokers/analyst having a mean score of 4.09, 3.98 and 3.90 respectively.

4.7.2 Three least preferred variables as source of information

Some of the variables as a source of information are not so important and hence, least

preferred by the investors. These three least preferred variables as a source of information

are corporate forecast prepared by independent investment company rating agencies‘

reports and Financial Press and newspapers, each is having a mean score of 3.51, 3.57

and 3.62 respectively.

4.7.3 Three most influencing informative variables on investment decision

For identifying the influence level of each variable mentioned in the Table 4.11, the mean

score of each variable‘s influence level was identified. Three variables that most

influence the investment decision are rating agencies‘ reports (mean score 4.17), annual

reports (mean score 4.09) and conversation /exchanges of views with company

executives and sector experts (mean score 3.97).

4.7.4 Three least influencing informative factors on investment decision

Out of total variables mentioned Table 4.11, three variables that least influence the

investment decision are corporate forecast prepared by independent investment company,

present investors and conversation/exchanges of views with professional colleagues

having mean score of 2.48, 2.88 and 2.94 respectively.

4.7.5 Gap Analysis

179

Gap in the mean score was identified by subtracting the mean score of variables for

which responses given on the basis of influence of these variables on investment decision

from the mean score of variables for which responses given on the basis of preference

towards a variable as a source of information. From the Table 4.11, it can be seen that

except two variables all the variables have positive gap, means except these two

variables, all other variables do not significantly influence the investors in their

investment decisions, as per their own preference given to the variables. The three most

positive gaps are for the variables ‗present investors‘ (1.21), ‗corporate forecast prepared

by independent investment company‘ (1.03) and ‗conversation/exchanges of views with

professional colleagues‘ (0.92). The highest gap is for the variable ‗present investors‘

which indicates that the preference of respondents is very high as compared to the

influence derived from this. Even respondents prefer to have more conversation with

professional colleagues with regard to investment decision, but the impact/influence of

this conversation on the investment decisions of investors is not profound, and hence, this

variable shows its presence among the top three gaps.

4.7.6 Paired „t‟–test

A paired sample t-test is the test for differences in the means of paired samples

(Malhorta, 2008326

). The t-test for differences between group mean can be conceptualized

as the difference between the mean divided by the variability of random means. The t-

value is a ratio of the difference between the two sample means and the standard error.

The t-test tries to provide a rational way of determining if the difference between the two

sample means occurred by chance (Hair et al., 2003327

). Some researchers refer to this

test as matched-pair test, or t test for related measures, or the correlated test (Black,

2006328

).

326 Malhotra, N.K. (2008). Marketing Research- An Applied Orientation(5th ed.). New Delhi: Pearson

Education, p. 453. 327 Hair J., Bush F., Robert, P., & Ortinau D. J. (2003). Marketing Research Within a Changing Information

Environment. Tata McGraw Hill Publication, New Delhi, Second edition, p. 542. 328 Black K. (2006). Business Statistics for Contemporary Decision Making (4th ed.). New Delhi: Wiley

India publication, p. 361.

180

Table 4.12 Paired Sample Statistics

Pairs Variables Mean Std.

Deviation

Std.

Error

Mean

Pair 1 Family members (P)* 3.78 0.801 0.041

Family members (I)** 3.58 1.059 0.054

Pair 2 Friends and relatives (P) 3.80 0.893 0.046

Friends and relatives (I) 3.73 1.155 0.059

Pair 3 Annual reports of the company(P) 3.68 0.889 0.045

Annual reports of the company(I) 4.09 0.693 0.035

Pair 4 Conversation /exchanges of views with professional

colleagues (P)

3.86 0.732 0.037

Conversation /exchanges of views with professional

colleagues (I)

2.94 1.123 0.057

Pair 5 Financial Press, newspapers and electronic media (P) 3.62 0.798 0.041

Financial Press, newspapers and electronic media (I) 2.97 1.049 0.053

Pair 6 Conversation /exchanges of views with company

executives and sector experts (P)

3.98 0.755 0.038

Conversation /exchanges of views with company

executives and sector experts (I)

3.97 0.649 0.033

Pair 7 Corporate forecast prepared by independent investment

company (P)

3.51 0.863 0.044

Corporate forecast prepared by independent investment

company (I)

2.48 0.857 0.044

Pair 8 Present investors (P) 4.09 0.665 0.034

Present investors (I) 2.88 1.111 0.057

Pair 9 Financial advisors/brokers and analyst‘s

recommendation (P)

3.90 0.722 0.037

Financial advisors/brokers and analyst‘s

recommendation (I)

3.67 0.598 0.030

Pair 10 Rating agencies‘ reports (P) 3.57 0.827 0.042

Rating agencies‘ reports (I) 4.17 0.601 0.031

P* stands for preference, I** stands for influence

For this study, pairs of ten variables between preference and influence on investment

decisions are used. The hypotheses used for this paired t-test are as under.

181

H0: There is no significant difference between preference for the selected informative


H1: There is a significant difference between preference for the selected informative


Paired t-test was performed for all the ten pairs under study and the output is represented

in Table 4.12.

Table 4.12 represents mean, standard deviation and standard error mean for all the ten

pairs of informative variables under study. From the standard deviation column, it is

found that for majority of variables these values are below 1.00. This indicates that the

variations in responses are low.

Table 4.13 represents the t-test values. In Table 4.13, second, third and fourth column

show the differences in mean, standard deviation and standard error of mean respectively.

Last column of the Table 4.13 represent the significance value for two tailed test.

182

Table 4.13 Paired Samples t-test values

Variables

Paired Differences

t-

value

Sig.

(2 tailed)

Mean

Std.

Deviation

Std.

Error

Mean

90%

Confidence

Interval of the

Difference

Lower

Upper

Family members 0.992 1.332 0.068 0.859 1.126 14.619 0.000*

Friends and

relatives

0.953 1.415 0.072 0.811 1.095 13.216 0.000*

Annual reports of

the company

-0.410 1.093 0.056 -0.520 -0.301 -7.364 0.000*

Conversation

/exchanges of

views with

professional

colleagues

0.925 1.351 0.069 0.789 1.060 13.430 0.000*

Financial Press,

newspapers and

electronic media

0.652 1.376 0.070 0.514 0.790 9.295 0.000*

Conversation

/exchanges of

views with

company

executives and

sector experts

0.008 1.022 0.052 -0.095 0.110 0.150 0.881

Corporate

forecast prepared

by independent

investment

company

1.031 1.237 0.063 0.907 1.155 16.356 0.000*

Present investors 1.216 1.272 0.065 1.088 1.343 18.754 0.000*

Financial

advisors/brokers

and analyst‘s

recommendation

0.031

0.935

0.048

-0.063

0.125

0.654

0.513

Rating agencies‘

reports

-0.603 0.960 0.049 -0.699 -0.506 -0.506 0.000*

*p<0.05, significant at 5%

The null hypothesis mentioned is tested at 95% level of confidence. From the last column

of Table 4.13, it is found that only for two pairs the significance value is greater than 0.05

and that is for ‗conversation/ exchanges of views with company executives and sector

183

experts‘ and ‗financial advisors/brokers and analyst‘s recommendation‘. For these

variables, null hypothesis is not rejected and it may be concluded that for conversation/

exchanges of views with company executives and sector experts and financial

advisors/brokers and analyst‘s recommendation, there is no significant difference

between their preference for and influence on investment decisions. For all other

variables, excluding two mentioned above, the difference between preference and

influence is significant at 5% level of significance, as the two tailed significance value is

less than 0.05.

4.8 Reliability and Normality of data

There were two questions in which the respondents were asked to give their 1) preference

to the variables as preferred source of information and 2) rate the influence of each

variable on their investment decisions. Before using these data for various

interdependence techniques, it is necessary to check whether the data is reliable, valid

and normally distributed.

4.8.1 Reliability of Measurement

Reliability is an assessment of the degree of consistency between multiple measurements

of a variable (Hair et al., 2009329

). It has to do with the accuracy and precision of a

measurement procedure (Cooper and Schindler, 2008330

).

Reliability is concerned with estimates of the degree to which a measurement is free of

random or unstable error. Reliable instruments can be used with confidence that transient

and situational factors are not interfering. They are robust; they work well at different

times under different conditions (Cooper and Schindler, 2009331

).

329 Hair, J. F., William, B. C., Barry, B. J., Anderson, R. E.& Tatham, R. L. (2009). Multivariate Data

Analysis (6th ed.). New Delhi: Pearson Education, p. 161. 330

Cooper, D. & Schindler, P. (2009). Business Research Methods (9th ed.). New Delhi : McGraw Hill

Publication, p. 320. 331 Ibid, p. 321.

184

The assessment of the consistency of the entire scale can be measured through reliability

coefficient. The most widely used reliability measure is Cronbach‘s alpha. Cronbach‘s

alpha is the average of all possible split half coefficients resulting from different ways of

the scale items. Hair et al. (2009) suggested the generally agreed upon lower limit for

Cronbach‘s Alpha is 0.7, although it may decrease to 0.60 in exploratory research (Hair

et al., 2009332

). The Cronbach‘s Alpha coefficient value for the scale 1) preference to the

16 variables as preferred source of information is 0. 708 as shown in Table 4.14 and 2) 44

variables influencing investment decision is 0.794 as shown in Table 4.15, indicates that

high level of internal consistency in the items. The values of Cronbach‘s Alpha is

acceptable and desirable, as these values are more than 0.700, confirming that both the

scales are reliable enough to be used for further analysis.

Table 4.14 Cronbach‟s Alpha for the Variables of Preferred Source of Information

Cronbach's Alpha Number of Items

0.708 16

Table 4.15 Cronbach‟s Alpha for Variables Influencing Investment Decision

Cronbach's Alpha Number of Items

0.794 44

4.8.2 Data quality and normality check

Data quality is examined by using skewness, Kurtosis and t-test values as shown in the

Table 4.16 and Table 4.17. A close examination of fifth column in Table 4.16 and Table

4.17 reveal that Kurtosis for majority of variables is below than 1. Out of 16 variables of

source of information, for all the variables, Kurtosis is below than 1 (see Table 4.16) and

out of 44 variables influencing investment decision only Kurtosis of eight factors are

greater than one and approaching to 2.00, a level beyond which non-normality of

distribution becomes a concern (see Table 4.17).


Analysis (6th ed.). New Delhi: Pearson Education, p. 161.

185

Table 4.16 Data Quality for Variables of Preferred Sources of Information

Variables

Mean

Std.

Deviation Skewness Kurtosis

t- test Sig.

(2

Tailed)

Certified financial planner 4.20 0.741 -0.796 0.638 111.11 0.00

Annual reports of the company 3.68 0.889 -0.632 0.591 81.310 0.00

Prospectus of a company 3.41 1.115 -0.391 -0.563 59.99 0.00

Company‘s website 3.59 0.789 -0.465 0.249 89.15 0.00

Distributer/ Agents of financial

products 3.93 0.677 0.089 -0.813

113.83

0.00

Rating agencies‘ report 3.57 0.827 -0.138 -0.505 84.71 0.00

Company‘s telephone

representatives 3.49 0.600 0.164 -0.374

114.02 0.00

Family members 3.78 0.801 0.175 -0.976 92.60 0.00

Friends and relatives 3.80 0.893 -0.672 0.329 83.44 0.00

Conversation /exchanges of

views with professional

colleagues

3.86 0.732 -0.381 0.093

103.54

0.00

Publication in financial press,

newspapers and electronic

media

3.62 0.798 -0.146 -0.407

89.12

0.00

Conversation /exchanges of

views with company executives

and sector experts

3.98 0.755 -0.728 0.717

103.38

0.00

Corporate forecast prepared by

independent investment

company

3.51 0.863 -0.740 0.773

79.88

0.00

Published reports of the

research agencies 3.49 1.011 -0.546 -0.017

67.73

0.00

Present investors 4.09 0.665 -0.424 0.410 120.71 0.00

Financial advisors/brokers and

analyst‘s recommendation 3.90 0.722 -0.225 -0.227

106.00

0.00

186

Table 4.17 Data Quality for Variables Influencing Investment Decision

Variables

Mean

Std.


t- test Sig. (2-

Tailed)

Condition of financial

statement 4.05 0.65 -0.05 -0.59 123.07 0.00

Expected Corporate

Earning 2.72 1.04 0.92 0.14 51.09 0.00

Past performance of the

firm 3.98 0.68 0.02 -0.83 114.86 0.00

Company‘s position in the

industry 3.91 0.69 0.12 -0.91 110.86 0.00

Insider‘s information 3.87 0.72 0.20 -1.07 105.09 0.00

Result of fundamental

analysis 2.94 1.19 0.46 -0.82 48.39 0.00

Result of technical

analysis 2.88 1.23 0.61 -0.75 45.90 0.00

Expected return on

investment 4.03 0.63 -0.02 -0.44 126.40 0.00

Feeling for a company 3.29 1.00 0.09 -0.96 64.29 0.00

Perceived ethics of

company 4.11 0.66 -0.12 -0.73 121.59 0.00

Political party affiliation 3.20 1.01 -0.02 -0.56 62.34 0.00

Contribution of a firm

towards social causes 3.22 0.96 0.04 -0.65 65.99 0.00

Coverage in the press 3.22 1.27 0.43 -1.51 49.53 0.00

Recent price movements

in a firm‘s stock/NAV 2.83 1.28 0.64 -0.86 43.44 0.00

Statements from

politicians and

governmental officials

3.29 0.87 0.07 -0.31 74.38 0.00

Fluctuations/developments

in the indices of the major

market

3.64 0.95 -0.35 -0.78 75.22 0.00

Current economic

indicators 3.26 0.82 -0.12 -0.28 78.31 0.00

Reputation of a company

in the domestic market 3.38 0.90 -0.36 -0.79 74.02 0.00

Reputation of a parent

company or sister concern 4.07 0.61 -0.04 -0.36 129.92 0.00

Environmental record 3.64 0.64 0.50 -0.67 111.03 0.00

Market capitalization of

company 3.83 0.83 -0.54 0.35 91.00 0.00


of views with professional

colleagues

2.94 1.12 0.89 -0.66 51.32 0.00

187

Variables

Mean

Std.


t- test Sig. (2-

Tailed)

Publication in the

financial press,

newspapers and electronic

media

2.97 1.05 0.79 -0.50 55.57 0.00


of views with company

executives and sector

experts

3.97 0.65 0.03 -0.61 120.03 0.00

Studying the portfolio

investments of other

market players

3.77 0.65 0.26 -0.69 114.68 0.00

Corporate forecast

prepared by independent

investment company

2.48 0.86 0.79 1.08 56.84 0.00

Economic forecasts by

research institutions 2.90 1.12 0.68 -0.43 50.73 0.00

Study of Annual Reports 4.09 0.69 -0.13 -0.91 115.83 0.00

Family members 3.58 0.95 -0.40 -0.25 74.07 0.00

Friends and relatives 3.73 0.95 -0.63 0.08 77.44 0.00

Present investors 3.67 0.89 -0.16 -0.73 80.53 0.00

Financial advisors/Broker

and analyst‘s

recommendation

3.87 0.60 0.05 -0.30 126.90 0.00

Rating agencies‘ reports 4.17 0.60 -0.09 -0.38 136.20 0.00

Diversification needs 4.14 0.71 -0.20 -0.98 115.05 0.00

Liquidity associated with

investment 2.91 1.26 0.08 -1.10 45.22 0.00

Availing the benefit of

income tax deduction 3.44 1.25 0.09 -1.62 54.11 0.00

Risk-return trade off 3.98 0.61 0.01 -0.33 127.20 0.00

Minimizing risk 4.01 0.64 -0.01 -0.51 123.79 0.00

Ease of obtaining

borrowed fund 3.03 1.42 -0.01 -1.38 41.67 0.00

Preferred investment time

horizon 2.74 1.15 0.42 -0.60 46.65 0.00

Safety associated with

investment 2.98 1.31 0.18 -1.16 44.59 0.00

Affordable minimum

investment amount 2.77 1.49 0.31 -1.40 36.55 0.00

Ease in liquidity 4.03 0.65 -0.03 -0.63 121.44 0.00

Guaranteed return 2.57 1.16 0.83 0.04 43.50 0.00

Table 4.17 Continued

188

Thus, according to Kurtosis, data for all the 16 variables of preferred sources of

information and 44 variables influencing investment decision are normally distributed.

Also, referring to fourth column of Table 4.16 and Table 4.17 indicate that, Skewness for

all the variables is less than 1 for 16 variables of preferred sources of information and the

Skewness for all the 44 variables influencing investment decision is less than 0.94, far

smaller than the lower bound of four or five. Thus, both Kurtosis and Skewness of the

variables provide indication that the data are distributed normally. The t-test scores, as in

the last column of Table 4.16 and Table 4.17, indicate that the mean score of the

respondents on five point Likert scale are significantly different for all 16 variables of

preferred sources of information and 44 variables influencing investment decision

respectively.

4.9 Factor Analysis

One of the most interdependent techniques for data reduction is factor analysis.

According to Luck and Rubin, factor analysis seeks to identify a set of dimensions that is

not readily observed in a large set of variables (Luck and Rubin, 2003333

). The analysis

summarizes a majority of the information in the data set in terms of relatively new few

categories, known as factors. Two basic reasons using factor analysis are (i) to simplify a

set of data by reducing a large number of measures (in which some may be interrelated

causing multicollinearity) for set of respondents to a smaller manageable number of

factors (which are not interrelated) that still retain most of the information found in the

original data set and (ii) to identify the underlying structure of the data in which a large

number of variables may really be measuring a small number of basic characteristics of

the sample.

According to Hair et al. (2003334

), factor analysis is a multivariate statistical technique

that is used to summarize the information contained in a large number of variables into a

333 Luck, D. &Rubin, D. (2003). Marketing Research (7th ed.). New Delhi: Prentice Hall of India Pvt. Ltd.,

542-548. 334 Hair, J. F., Bush, R. P. & Ortinau, D. J. (2003). Marketing Research – Within a Changing Information

Environment (2nd ed.). New Delhi: Tata McGraw Hill Publishing Company Ltd., p. 601.

189

smaller number of subsets or factors. Reasons given by Malhotra Naresh K. (2008335

) for

using factor analysis are (1) to identify underlying dimensions or factors, which explain

the correlation among a set of variables, (2) to identify a new smaller set of uncorrelated

variables to replace the original set of correlated variables and (3) to identify a smaller set

of salient variables from a larger set. For the current study, factor analysis is used to

reduce the number of variables that (1) are preferred by respondents as source of

information and (2) may influence investment decision of respondents. Respondents were

asked to give their preference (on the five point Likert scale, where 1- Not preferred and

5- the most preferred) for source of information on 16 variables. On the other hand,

respondents were asked to rate the influence of 44 variables (on the five point Likert

scale, where 1- Least influence and 5-Most significantly influence) on their investment

decision. Factor analysis was performed separately for these two types of variables under

study.

4.9.1 Factor analysis for variables preferred by investors as source of information

Following the Cronbach‘s Alpha for the 16 variables of preferred sources of information

as shown in Table 4.14, which is 0.708 and data quality, which is examined by using

Skewness, Kurtosis and t-test values as shown in Table 4.16 explained both Kurtosis and

Skewness of the variables provide indication that the data are distributed normally. The t-

test values, as shown in the last column of Table 4.16, indicate that the mean scores of the

respondents on five point Likert scale are significantly different for all 16 variables of

preferred source of information. Hence, these allow the researcher to perform factor

analysis for these 16 variables of preferred source of information.

4.9.1.1 Bartlett‟s test of Sphericity

The method of determining the appropriateness of the factor analysis examines the entire

correlation matrix. The Bartlett‘s test of Sphericity is a statistical test for measuring the

335 Malhotra, N.K. (2008). Marketing Research – An Applied Orientation (5th ed.). New Delhi: Pearson

Education, pp. 640-641.

190

presence of correlations among the variables (Hair et al., 2009336

). It is used to test the

null hypothesis that the variables are uncorrelated in the population (Malhotra, 2008337

).

Means, it provides the statistical significance that the correlation matrix has significant

correlations among at least some of the variables. As, shown in Table 4.18, the Bartlett‘s

test of Sphericity value 1.671 with significance level of is 0.000, satisfies the required

condition. This indicates the statistical significance that correlation matrix has significant

correlation among other variables.

Table 4.18 KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.664

Bartlett's Test of Sphericity Approx. Chi-Square 1.674

Df 120

Sig. 0.000


The Kaiser-Meyer-Olkin (KMO) Measure for Sampling Adequacy is an index used to

examine the appropriateness of factors analysis. It is an index to quantify the degree of

inter-correlations among the variables. This examines the appropriateness of factor

analysis. It compares the magnitudes of observed correlation coefficients to magnitude of

partial correlation coefficients. The KMO value varies from 0 to 1. High value (between

0.5 to 1.0) indicates factor analysis is appropriate. Small values of KMO Statistic indicate

that correlations between pairs of variables cannot be explained by other variables, and

hence, factor analysis is not suitable (Malhotra, 2008338

). As shown in Table 4.18, the

KMO value for variables preferred by respondents as source of information is 0.664,

which is nearer to 1.0. Hence, this value is acceptable and justifies the appropriateness of

factor analysis.

336 Hair, J. F., William, B. C., Barry, B. J., Anderson, R. E.& Tatham, R. L. (2009). Multivariate Data Analysis (6th ed.). New Delhi: Pearson Education, 138. 337 Malhotra, N. (2008). Marketing Research: An Applied Orientation (5th ed.). New Delhi: Pearson

Education, p. 644. 338 Malhotra N. (2008). Marketing Research – An Applied Orientation (5th ed.). New Delhi: Pearson

Education, p. 642.

191

4.9.1.3 Anti-Image Correlation Matrix

It is the matrix of the partial correlations among variables after factors analysis,

representing the degree to which the factors explain each other in the results (Hair et al.,

2009339

). The diagonal values in the Anti-Image Correlation Matrix represent MSA

value. The variable(s) with the value less than 0.5 should be omitted from factor analysis

one by one, with the smallest being considered omitted first. The values which are not on

the diagonal represent the partial correlations among the variables.

Table 4.19 indicates that all the variables have MSA value more than 0.5. Hence,

researcher can proceed further.

Table 4.19 Anti- Image Correlation Matrix

IS1 IS2 IS3 IS4 IS5 IS6 IS7 IS8 IS9 IS10 IS11 IS12 IS13 IS14 IS15 IS16

IS1 0.636 0.032 0.060 -0.166 0.070 -0.039 -0.046 0.242 -0.258 -0.084 -0.029 -0.408 -0.242 -0.048 -0.200 0.040

IS2 0.032 0.687 -0.283 -0.132 0.131 -0.133 0.173 -0.141 -0.317 0.053 -0.321 -0.147 0.075 -0.292 0.143 0.201

IS3 0.060 -0.283 0.733 -0.361 -0.182 -0.032 -0.076 0.028 0.274 -0.228 -0.091 -0.118 -0.216 -0.050 -0.022 0.034

IS4 -0.166 -0.132 -0.361 0.757 0.072 -0.173 -0.171 -0.053 -0.022 -0.057 -0.216 0.168 0.119 0.077 0.131 -0.162

IS5 0.070 0.131 -0.182 0.072 0.530 0.081 0.251 -0.048 -0.148 -0.018 0.122 0.119 0.162 -0.259 -0.082 -0.260

IS6 -0.039 -0.133 -0.032 -0.173 0.081 0.738 -0.007 0.038 -0.150 0.019 0.183 0.016 -0.230 -0.161 0.114 -0.117

IS7 -0.046 0.173 -0.076 -0.171 0.251 -0.007 0.611 -0.070 -0.048 -0.002 -0.106 -0.036 0.018 -0.108 -0.152 0.223

IS8 0.242 -0.141 0.028 -0.053 -0.048 0.038 -0.070 0.526 -0.261 -0.033 0.102 -0.023 -0.046 -0.025 -0.186 0.056

IS9 -0.258 -0.317 0.274 -0.022 -0.148 -0.150 -0.048 -0.261 0.558 0.053 -0.029 -0.097 0.197 0.174 -0.274 -0.096

IS10 -0.084 0.053 -0.228 -0.057 -0.018 0.019 -0.002 -0.033 0.053 0.767 -0.006 0.070 0.082 -0.129 -0.057 0.069

IS11 -0.029 -0.321 -0.091 -0.216 0.122 0.183 -0.106 0.102 -0.029 -0.006 0.737 0.239 0.061 -0.128 0.004 -0.137

IS12 -0.408 -0.147 -0.118 0.168 0.119 0.016 -0.036 -0.023 -0.097 0.070 0.239 0.588 0.020 -0.053 0.064 -0.220

IS13 -0.242 0.075 -0.216 0.119 0.162 -0.230 0.018 -0.046 0.197 0.082 0.061 0.020 0.565 -0.120 -0.147 -0.002

IS14 -0.048 -0.292 -0.050 0.077 -0.259 -0.161 -0.108 -0.025 0.174 -0.129 -0.128 -0.053 -0.120 0.733 -0.092 -0.158

IS15 -0.200 0.143 -0.022 0.131 -0.082 0.114 -0.152 -0.186 -0.274 -0.057 0.004 0.064 -0.147 -0.092 0.626 -0.139

IS16 0.040 0.201 0.034 -0.162 -0.260 -0.117 0.223 0.056 -0.096 0.069 -0.137 -0.220 -0.002 -0.158 -0.139 0.561


Communality is the amount of variance a variable explains with all the factors being

considered. This is also the percentage of total variance explained by the common

factors (Malhotra, 2008340

). The method selected for conducting factor analysis here is


Analysis (6th ed.). New Delhi: Pearson Education, p. 125. 340 Malhotra N. (2008). Marketing Research – An Applied Orientation (5th ed.). New Delhi: Pearson

Education, p. 561.

192

Principal Component Analysis. In this method, the total variance in the data is

considered. The initial communalities for Principal Component Analysis are 1. However,

the primary concern is the extracted communalities, which are achieved after extraction

of factors. The communalities can be found mathematically by squaring the factor

loading of a variable across all variables and then summing these figures. This term may

be interpreted as a measure of ‗uniqueness‘. In the present study, for the variables

preferred by respondents as source of information, the communalities are calculated with

the help of computer software as shown in Table 4.20. A low communality figure

indicates that the variables is statistically independent and cannot be combined with other

variables.

4.20 Communalities

Variables Initial Extraction

Communalities

IS1 1.000 0.656

IS2 1.000 0.734

IS3 1.000 0.693

IS4 1.000 0.642

IS5 1.000 0.716

IS6 1.000 0.444

IS7 1.000 0.603

IS8 1.000 0.530

IS9 1.000 0.773

IS10 1.000 0.483

IS11 1.000 0.581

IS12 1.000 0.582

IS13 1.000 0.609

IS14 1.000 0.575

IS15 1.000 0.711

IS16 1.000 0.586

Extraction Method: Principal Component Analysis.

The close observation of Table 4.20 shows that the communality for variable IS6 (i.e.

Rating agencies‘ reports) and IS10 (i.e. Conversation/exchanges of views with

professional colleagues) is 0.444 and 0.483 respectively, which are removed from the list

193

of 16 variables of information sources and Anti-Image Correlation Matrix is to be

developed, MSA values are observed (Table 4.21), and revised communalities extracted

and presented in Table 4.22, shows that revised extracted communalities for the rest of

the variables are high (greater than 0.5), and hence, acceptable for all variables to

proceed.

Table 4.21 Revised Anti- Image Correlation Matrix

IS1 IS2 IS3 IS4 IS5 IS7 IS8 IS9 IS11 IS12 IS13 IS14 IS15 IS16

IS1 0.613 0.032 0.041 -0.181 0.072 -0.047 0.242 -0.264 -0.023 -0.404 -0.253 -0.066 -0.203 0.042

IS2 0.032 0.656 -0.285 -0.156 0.145 0.175 -0.135 -0.348 -0.304 -0.151 0.041 -0.317 0.165 0.185

IS3 0.041 -0.285 0.702 -0.395 -0.190 -0.079 0.022 0.293 -0.091 -0.105 -0.215 -0.088 -0.033 0.048

IS4 -0.181 -0.156 -0.395 0.726 0.087 -0.175 -0.049 -0.046 -0.191 0.178 0.088 0.044 0.151 -0.183

IS5 0.072 0.145 -0.190 0.087 0.524 0.252 -0.052 -0.137 0.109 0.120 0.188 -0.254 -0.094 0.252

IS7 -0.047 0.175 -0.079 -0.175 0.252 0.595 -0.070 -0.050 -0.107 -0.036 0.017 -0.112 -0.153 0.224

IS8 0.242 -0.135 0.022 -0.049 -0.052 -0.070 0.530 -0.257 0.097 -0.021 -0.035 -0.024 -0.194 0.064

IS9 -0.264 -0.348 0.293 -0.046 -0.137 -0.050 -0.257 0.551 -0.001 -0.100 0.165 0.162 -0.259 -0.120

IS11 -0.023 -0.304 -0.091 -0.191 0.109 -0.107 0.097 -0.001 0.766 0.242 0.109 -0.104 -0.018 -0.118

IS12 -0.404 -0.151 -0.105 0.178 0.120 -0.036 -0.021 -0.100 0.242 0.574 0.018 -0.043 0.067 -0.225

IS13 -0.253 0.041 -0.215 0.088 0.188 0.017 -0.035 0.165 0.109 0.018 0.555 -0.154 -0.120 -0.037

IS14 -0.066 -0.317 -0.088 0.044 -0.254 -0.112 -0.024 0.162 -0.104 -0.043 -0.154 0.710 -0.084 -0.174

IS15 -0.203 0.165 -0.033 0.151 -0.094 -0.153 -0.194 -0.259 -0.018 0.067 -0.120 -0.084 0.640 -0.123

IS16 0.042 0.185 0.048 -0.183 -0.252 0.224 0.064 -0.120 -0.118 -0.225 -0.037 -0.174 -0.123 0.557

Table 4.21 shows that all variables in the table have MSA value more than 0.5. So,


Table 4.22 Revised Communalities


Communalities

IS1 1.000 0.738

IS2 1.000 0.714

IS3 1.000 0.697

IS4 1.000 0.644

IS5 1.000 0.707

IS7 1.000 0.593

IS8 1.000 0.644

IS9 1.000 0.784

IS11 1.000 0.607

IS12 1.000 0.679

IS13 1.000 0.707

194

IS14 1.000 0.609

IS15 1.000 0.679

IS16 1.000 0.596



The most commonly used method to answer the key question: How many factors to

extract or retain?

The rational for the latent roots or eigenvalues criterion is that any individual factor

should account for the variance of at least a single variable if it is to be retained for

interpretation. It is required that the scale constructed and the components extracted

should be able to explain maximum variance in the data. For this study, an analysis of the

Eigen values is required. Eigenvalues are the sum of the variances of the factor values.

Eigen value represents the total variance explained by each factor. Hence, only factors

with a variance greater than 1.0 are considered significant; all factors with eigenvalues

less than 1.0 are considered insignificant and are disregarded (Malhotra, 2008341

). Using

eigenvalues for establishing a cut off is most reliable when number of variables is

between 20 to 50 (Hair, 2009342

).

The percentage of variance is an approach based on achieving a specified cumulative

percentage of total variance extracted by successive factors. The purpose is to ensure

practical significance for the derived factors by ensuring that they explain at least

specified amount of variance. In the social science, it is common to consider a solution

that accounts for 60 percent of the total variance as satisfactory (Hair, 2009343

).

341 Malhotra N. (2008). Marketing Research – An Applied Orientation (5th ed.). New Delhi: Pearson

Education, p. 561. 342 Hair, J. F., William, B. C., Barry, B. J., Anderson, R. E.& Tatham, R. L. (2009). Multivariate Data

Analysis (6th ed.). New Delhi: Pearson Education, p. 144. 343 Ibid, 144.

195

Table 4.23 shows that the Eigenvalues of all the factors that can be extracted. Table 4.23

also shows the cumulative variance. However, it is required that the maximum amount of

variance should be explained in minimum number of components – for this reason

extraction of the components is required. Only those factors are extracted for which

Eigen values are greater than one. Thus, the factors extracted out of 14 variables under

study are five in number and together contribute 67.12% of total variance. This is a fair

percentage of variance to be explained and assumes the appropriateness of the factor

analysis. Thus, researcher has extracted 5 dimensions from total 14 variables preferred by

respondents as source of information for investment decision.

Further, Table 4.23 shows the extraction sum of squared loadings of the scale constructed

for variables/factors preferred by respondents. However, a careful look at Table 4.23

shows that 67.12% variance is not uniformly distributed across all the components, where

only first component accounts for 20.13% of variance. Thus, in order for the variance to

be uniformly distributed across the components, a rotation of the components matrix is

required.

196

Table 4.23 Total Variance Explained

Comp

onent

Initial Eigenvalues

Extraction Sums of

Squared Loadings

Rotation Sums of Squared

Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 3.008 21.483 21.483 3.008 21.483 21.483 2.819 20.135 20.135

2 2.284 16.316 37.798 2.284 16.316 37.798 1.874 13.385 33.520

3 1.640 11.718 49.516 1.640 11.718 49.516 1.717 12.264 45.785

4 1.413 10.093 59.609 1.413 10.093 59.609 1.617 11.549 57.333

5 1.052 7.511 67.120 1.052 7.511 67.120 1.370 9.787 67.120

6 0.877 6.268 73.388

7 0.678 4.845 78.233

8 0.655 4.676 82.909

9 0.589 4.208 87.118

10 0.471 3.361 90.479

11 0.408 2.913 93.392

12 0.393 2.810 96.202

13 0.280 2.001 98.203

14 0.252 1.797 100.000



There are two types of extraction methods.

1. Principal Component Analysis and 2. Common Factor Analysis

Principal component analysis considers the total variance in the data and derives the

factors than contain small proportions of unique variance and in some instances, error

variance. This method is most appropriate when data reduction is primary concern,

focusing on the minimum number of factors needed to account for the maximum portion

of the total variance represented in the original set of the variables (Hair, 2009344

).



197

In common factor analysis, the factors are estimated based only on the common or shared

variance, assuming that both the unique and error variance are not of interest in defining

the structure of the variables. Communalities are inserted in the diagonal of the

correlation matrix to employ common variance in the estimation of the factors. This

method is most appropriate when primary objective is to identify the underlying

dimensions and the common variance is of interest (Hair, 2009345

).

The objective of this study is to extract the factors and so the data reduction becomes the

primary concern. Hence, the principal component analysis method is used to extract the

unrotated component matrix.

Table 4.24 Component Matrixa

Variables

Components

1 2 3 4 5

IS2 0.770 -0.066 0.146 0.217 -0.221

IS4 0.740 -0.268 0.083 0.094 -0.090

IS3 0.728 -0.289 0.119 -0.223 0.138

IS11 0.662 -0.311 0.188 0.172 -0.082

IS14 0.141 0.616 0.280 -0.278 0.231

IS15 0.064 0.673 -0.089 0.121 0.446

IS9 0.193 0.667 0.027 0.499 -0.228

IS12 0.238 0.574 -0.317 -0.206 -0.338

IS1 0.415 0.523 -0.459 -0.183 -0.220

IS16 0.135 0.503 0.452 -0.330 -0.106

IS5 -0.112 0.350 0.716 -0.180 0.164

IS7 0.353 -0.124 -0.506 0.300 0.326

IS8 0.117 0.321 0.169 0.600 0.373

IS13 0.282 0.115 -0.403 -0.520 0.427


a. 5 components extracted. 345 Ibid, 142

198

4.9.1.7 Factor Loading

A factor loading represents the correlations between the factors and variables. It shows

the strength of the variables that compose the factor. The larger the absolute value of the

factor loading, the factor and the variable are more closely related. Means, the more

important role the variable plays in interpreting the factor analysis (Malhotra, 2008346

).

Table 4.25 guides the researcher for identifying significant factor loadings based on

sample size.

Table 4.25 Guidelines for Identifying Significant Factor Loadings based on Sample

Sizea

Factor Loading Sample size needed for

significance

0.30 350

0.35 250

0.40 200

0.45 150

0.50 120

0.55 100

0.60 85

0.65 70

0.70 60

0.75 50 (a Significance is based on a .05 significance level, a power level of 80 percent, and

standard errors assumed to be twice those of conventional correlation coefficient)

(Source: Hair, et al. (2009). Multivariate Data Analysis (6th ed.).Pearson Education,

New Delhi, p. 152)

The sample size taken by researcher is 385 for this study. Hence, factor loading 0.30 is

sufficient. But, the factor loading value greater than 0.50 is generally considered

necessary for practical significance (Hair, 2009347

). Hence, the researcher has considered

factor loading 0.5 for extracting the factors from the list of total 16 variables as preferred

346

Malhotra N. (2008). Marketing Research – An Applied Orientation (5th ed.). New Delhi: Pearson

Education, p. 561. 347 Hair, J. F., William, B. C., Barry, B. J., Anderson, R. E.& Tatham, R. L. (2009). Multivariate Data


199

by respondents as source of information. He further added that a ―Although factor

loading of +.30 to +.40 are minimally acceptable for its significance. To be considered

significant, a smaller loading is needed given either a larger sample size or on a larger

number of variables being analyzed‖ (p. 153). Hence, researcher has considered factor

loading of 0.4 for extracting the factors from the list of total 44 variables that influencing

investment decision of investors.

4.9.1.8 Rotated Factor Matrix

Components matrix (unrotated matrix) is the loadings of various variables to the

extracted components, which is shown in Table 4.24. Although the initial or unrotated

matrix as shown in Table 4.24 indicates the relationship between the factors and

individual variables, it seldom results in factors that can be interpreted, because the

factors are correlated with many variables. In such a complex matrix, it is difficult to

interpret the factors. Therefore, through rotation, the factor matrix is transformed into a

simpler one that is easier to interpret (Malhotra, 2008348

). Rotation of the factors

improves interpretation by reducing some of the ambiguities that often accompany initial

unroated factor solutions. Therefore, researcher must employ a rotational method to

achieve simpler and theoretically more meaningful factor solutions.

Mainly, there are two types of factor rotation methods:

1. Orthogonal factor rotation: In orthogonal factor rotation, the axes are maintained at

90 degrees. It is also possible to rotate the axes and not retain the 90-degree angle

between the reference axes. This is the simplest and more widely used approach for

factor rotation.

2. Oblique factor rotation: When 90-degree is not maintained it is called oblique factor

rotation. This method is not widely used because the analytical procedures for


Education, p.647.

200

performing the oblique rotations are not as well developed and are still subject to

some controversy.

Therefore, researcher has employed the orthogonal factor rotation method.

One of the three types of orthogonal rotation methods are: (1) Quartimax rotation – The

ultimate goal of Quartimax rotation is to simplify the row of a factor matrix, i.e.,

Quartimax focuses on rotating the initial factor so that a variable loads high on one factor

and as low as possible on all other factors. (2) Varimax rotation – This is method of

factor rotation that minimizes the number of variables with higher loadings on a factor,

thereby enhancing the interpretability of factors and has proved successful as an

analytical approach to obtain an orthogonal rotation of factors. Furthermore, the Kaiser‘s

experiment indicates that the factor pattern obtained by Varimax rotation tends to be

more invariant than pattern obtained by the Quarimax method when different subsets of

variables are analyzed. (3) Equipmax rotation – This approach is a compromise between

the Quarimax and Varimax approaches. Rather than concentrating either on

simplification of the rows or on simplification of columns, it tries to accomplish some of

each. This method has not gained widespread acceptance and is used infrequently

(Malhotra, 2008349

).

Therefore, for this study, researcher has used VARIMAX rotation method, which is the

most commonly used rotation method. The variance explained by each component before

and after the rotation method is shown in Table 4.23. It can be seen from this table that

the variance is now evenly distributed in a range of 20.13% - 9.78%, which was

previously 21.48% - 7.51%.

An analysis of factor loadings in the rotated factor matrix helps in interpreting and

naming the five factors that have been extracted in the earlier section. Interpretation is

done by identifying the variables that have very high loading in the same component.


Education, pp. 648-649.

201

These factors can be interpreted in terms of the variables that load highly on it. Table

4.26 shows the rotated component matrix.

The relationship between the observed variables and the newly produced factors is

revealed in the form of factor loadings. These are the coefficients within the matrix that

indicate the importance of the factor. These loadings have the lower limit of -1.0 and an

upper limit of +1.0. For better data reduction, those variables that have the factor loadings

more than 0.50 were considered under each factor. Fortunately, all the 14 variables have

factor loading more than 0.50, so all the 14 variables are considered for loading on

extracted five factors.

Table 4.26 Rotated Component Matrixa

Variables

Components

1 2 3 4 5

IS2 0.802 0.201 -0.023 0.105 -0.138

IS4 0.792 0.041 -0.113 -0.028 0.025

IS11 0.768 -0.073 -0.077 0.001 -0.072

IS3 0.740 -0.058 0.028 -0.124 0.360

IS12 -0.018 0.817 0.087 -0.006 0.055

IS1 0.108 0.811 -0.075 0.079 0.239

IS14 0.077 0.538 0.363 0.124 0.409

IS5 -0.058 -0.181 0.793 0.206 0.002

IS16 0.064 0.272 0.713 0.068 0.061

IS7 0.230 0.036 -0.615 0.295 0.271

IS8 0.083 -0.119 -0.005 0.781 -0.114

IS15 -0.193 0.248 0.138 0.679 0.317

IS9 0.062 0.516 0.098 0.601 -0.378

IS13 0.022 0.202 -0.089 -0.047 0.810


Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations.

Table 4.26 represents the rotated component matrix. Loadings of all the variables are

more than 0.5 with five factors extracted. The eigenvalues of the first five factors as

shown in Table 4.23 is more than 1 and total variance explained by these five factors is

67.12 percent.

202

The factors extracted, their respective items with the assigned codes and their

corresponding factor loading are given in Table 4.27.

Table 4.27 Composition of Each Factor Identified in Factor Analysis

Factor Items Factor

loadings

Factor 1

Published

Operational

Information

Annual Reports of the company (IS2) 0.802

Company‘s website (IS4) 0.792

Publication in the financial press, newspaper and

electronic media (IS11) 0.768

Prospectus of the company (IS3) 0.740

Factor 2

Independent

Information

Conversation/exchanges of views with company

executives and sector experts (IS12) 0.817

Certified Financial Planner (IS1) 0.811

Published reports of research agencies (IS14) 0.538

Factor 3

Advocate

Recommendation

Distributers/agents of financial products (IS5) 0.793

Financial advisors/brokers/ and analyst‘s

recommendations (IS16) 0.713

Company‘s telephonic representatives (IS7) -0.601

Factor 4

Accessibility

Information

Family members (IS8) 0.781

Existing investors (IS15) 0.679

Friends and relatives (IS9) 0.601

Factor 5

Performance

Forecast

Corporate forecast prepared by independent investment

company (IS13) 0.810

4.9.1.9 Naming of the factors

The following five factors were identified as per the factor loading in Table 4.27. The

explanation for the same is given below.

Factor 1: Published Operational Information

The four variables were identified under factor 1 are ‗annual reports of the company‘

(0.802), ‗company‘s website‘ (0.792), ‗publication in the financial press‘, ‗newspapers

203

and electronic media‘ (0.768) and ‗prospectus of the company‘ (0.740). The group of

these variables is named as ―Published Operational Information‖, as these variables

indicate the operational performance of a company and therefore are a key information

source for an investor looking to invest. Moreover, this operational performance is

published as information and available at free of cost to the investors. This extracted

factor explains 20.13 % of variance, which is the highest among the all factors.

Lin (2002) suggests investors collect the financial information from impersonal sources

that are written material published in books, brochures, reports, magazine; media such

as, TV, radio programs and the Internet.

Factor 2: Independent Information

The three variables identified under Factor 2 are ‗conversation/ exchanges of views with

company executives and sector experts‘ (0.817), ‗published reports from research

agencies‘ (0.811) and ‗certified financial planner‘ (0.538). By considering this, the name

of this factor is given as ―Independent Information‖. The variables under this factor are

related with an outside expert‘s view about the firm‘s position and what they perceive

about the firm and its prospects. In addition to this, the variables under this factor give

neutral and/or independent opinion to the investors with regard to the investment

alternatives/asset specific information about various investment choices available for

investment. This extracted factor explains 13.39 % of variance.

Arlen et al. (2007350

) emphasized that due to lack of confidence, investors heavily rely on

financial advice. Sung and Sandager (1997351

) prefer those sources of information, which

are be affiliated with an independent financial firm and provide neutral opinion.

Factor 3: Advocate Recommendation

350 Arlen, C. Ponston, L. R. & Akbulut, A. Y. (2007). Advice availability and gender differences in risky

decision making: A study of online retirement planning. Proceedings of the 40th Hawai International

Conference on System Sciences. 351 Sung, B. C. & Sandager, J. P. (1997). What consumers look for in financial planners? Association for

Financial Counseling and Planning Education.

204

The three variables identified under Factor 3 are ‗distributers/agents of financial

products‘ (0.793), ‗financial advisors/brokers and analyst‘s recommendation‘ (0.713) and

‗company‘s telephone representatives‘ (-0.615). The name of this factor is identified as

―Advocate Recommendation‖. The variables under this factor seek to give an inside

view of the firm, where views of people who have a direct or indirect stake in the

company are taken into consideration. These three variables together explain 12.26 % of

total variance.

Lin (2002) suggests that investors collect the financial information from personal sources

such as, professional financial services providers, brokers, distributers and third party

agents. Nick et. al (2010352

) found that telephone representatives of a company are one of

the major source to get the financial information.

Factor 4: Accessibility Information

The three variables identified under Factor 4 are ‗family members‘ (0.781), ‗existing

investors‘ (0.679) and ‗friends and relatives‘ (0.601). The name of this factor is identified

as ―Accessibility Information‖. These variables underpin information which can be

easily accessed by the investor although such information may need to be independently

verified. This extracted factor explains 11.59 % of variance.


) has stated that investors tend to rely heavily on the easily

available and accessible information. They don‘t tend to check the reliability of this

information and prefer to those piece of information which are easy to incorporate into

their decisions. They also added that investors tend to discount the information that seems

complex to incorporate into their decisions-making process, and adopt only those

information, which are easily available, accessible and adjustable in nature. Thus, they

352 Chater, N., Huck, S. &Inderest, R. (2010). Consumer Decision-Making in Retail Investment Services: A

Behavioural Economics Perspective. Decision Technology Ltd. 353

Chandra, A. &Kumar, R. (2011). Determinants of individual investor behaviour: An orthogonal linear




205

heavily rely on the easily available and accessible information. This accessible

information is easily available from family members, friends and relative and existing

investors.

Factor 5: Performance Forecast

The only one variable identified under factor 5 is corporate forecast prepared by

‗corporate forecast prepared by independent investment company‘ (0.810). This factor is

related to the business performance forecast of the company prepared by an independent

investment company. Hence, the name given to this extracted factor is “Performance

Forecast”, as financial information is supposed to facilitate the prediction of firm‘s

future cash flows and help the investors to assess the future securities risk and return.

This extracted factor explains 9.79 % of variance.

The psychological phenomenon explains the reasons for which why do investors behave

irrationally. One of the reasons is representativeness heuristic, which explains that after a

series of positive earnings, the investor is most likely started to believe that the next

period earnings will again be positive and fail to consider the probability of a decrease.

For this reason, they always want independent performance forecast of the firm, in which

they want to invest.

4.9.1.10 Mean score of extracted factors

Table 4.28 represents the factor wise mean preference score. The score is derived by

taking the grand mean of variables clubbed in each factor. From Table 4.28, it is found

that for factor 2 and factor 4, the mean score is highest, i.e. 3.89. This indicates that the

independent information and accessibility information are the most preferred by the

respondents, which is followed by the mean score of factor 3, i.e. advocate

recommendation, for which the preference mean score is 3.77. The least score is for

factor 5 and it is 3.51. This indicates that performance forecast is the least preferred by

206

the respondents to gather the information for their investment decision. The mean score

of the factor 1, i.e. ―Published operational information‖ is on the middle of the road.

Table 4.28 Mean Preference Score of Extracted Factors

Factor Factor Name Grand Mean Value

Factor 1 Published operational information 3.58

Factor 2 Independent information 3.89

Factor 3 Advocate recommendation 3.77

Factor 4 Accessibility information 3.89

Factor 5 Performance forecast 3.51

4.9.2 Factor analysis for variables influencing investment decision

Following the Cronbach‘s Alpha for the 44 variables influencing investment decision as

shown in Table 4.15, which is 0.794 and data quality, which is examined by using

Skewness, Kurtosis and t-test values as shown in Table 4.17 explained both Kurtosis and

Skewness of the variables provide indication that the data are distributed normally. The t-

test values, as shown in the last column of Table 4.17, indicate that the mean scores of the

respondents on five point Likert scale are significantly different for all 44 variables

influencing investment decision. Hence, all allow the researcher to perform factor

analysis for the 44 variables influencing investment decision of the respondents.

4.9.2.1 Bartlett‟s test of sphericity

The Bartlett‘s Test of Sphericity for measuring the presence of correlations among the

variables influencing investment decision is shown in Table 4.29. As shown in the Table

4.29 Bartlett's Test of Sphericity is 4.998 with significant value of 0.000. Hence,

researcher can proceed for the factor analysis.


KMO measure of sampling adequacy needs to be greater than 0.5 as per standards which

are present in this case. As shown in Table 4.29 the KMO value for factors influencing

207

investment decision is 0.690, which is nearer to 1.0. Hence, this value is acceptable and

justifies the appropriateness of factor analysis.

Table 4.29 KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.690

Bartlett's Test of

Sphericity

Approx. Chi-Square 4.998

df 946

Sig. 0.000

4.9.2.3 Measure of Sampling Adequacy

The MSA values for all the variables under study are checked with the help of Anti-

image correlation matrix and it is found that all variables have MSA value more than 0.5.

Hence, researcher can proceed further.


In the present study, for the variables influencing investment decision, the factor analysis

has been run on all 44 variables. Anti- image correlation matrix is derived and

communalities for all 44 variables are calculated with the help of computer software as

shown in Table 4.30. A low communality figure indicates that the variable is statistically

independent and cannot be combined with other variables.

208

Table 4.30 Communalities


ID1 1.000 0.661

ID2 1.000 0.467

ID3 1.000 0.681

ID4 1.000 0.596

ID5 1.000 0.754

ID6 1.000 0.632

ID7 1.000 0.623

ID8 1.000 0.587

ID9 1.000 0.581

ID10 1.000 0.639

ID11 1.000 0.677

ID12 1.000 0.706

ID13 1.000 0.557

ID14 1.000 0.520

ID15 1.000 0.655

ID16 1.000 0.434

ID17 1.000 0.711

ID18 1.000 0.674

ID19 1.000 0.435

ID20 1.000 0.496

ID21 1.000 0.554

ID22 1.000 0.517

ID23 1.000 0.613

ID24 1.000 0.604

ID25 1.000 0.555

ID26 1.000 0.471

ID27 1.000 0.658

ID28 1.000 0.634

ID29 1.000 0.659

ID30 1.000 0.710

ID31 1.000 0.712

209


ID32 1.000 0.641

ID33 1.000 0.621

ID34 1.000 0.612

ID35 1.000 0.635

ID36 1.000 0.505

ID37 1.000 0.480

ID38 1.000 0.587

ID39 1.000 0.702

ID40 1.000 0.578

ID41 1.000 0.667

ID42 1.000 0.733

ID43 1.000 0.599

ID44 1.000 0.392


A look at Table 4.30 shows the communality for ID2 (expected corporate earning) 0.467;

ID16 (fluctuations/developments in the indices of the major market), 0.434; ID19

(reputation of a parent company or sister concern), 0.435); ID20 (environmental record)

0.496; ID26 (corporate forecast prepared by independent investment company), 0.471;

ID37 (risk-return trade off), 0.480 and ID44 (guaranteed return), 0.392 are lower than

0.5. Hence, these variables are removed from the list of 44 variables and further analysis

was done. The revised Anti-image correlation matrix was studied by considering

remaining variables after removing above mentioned seven variables and new

communalities were found as shown in Table 4.31.


210



ID1 1.000 0.665

ID3 1.000 0.607

ID4 1.000 0.538

ID5 1.000 0.450

ID6 1.000 0.614

ID7 1.000 0.638

ID8 1.000 0.590

ID9 1.000 0.534

ID10 1.000 0.612

ID11 1.000 0.599

ID12 1.000 0.697

ID13 1.000 0.457

ID14 1.000 0.469

ID15 1.000 0.519

ID17 1.000 0.733

ID18 1.000 0.476

ID21 1.000 0.557

ID24 1.000 0.516

ID23 1.000 0.441

ID24 1.000 0.626

ID25 1.000 0.391

ID27 1.000 0.489

ID28 1.000 0.616

ID29 1.000 0.602

ID30 1.000 0.686

ID31 1.000 0.586

ID32 1.000 0.648

ID33 1.000 0.558

ID34 1.000 0.564

ID35 1.000 0.581

ID36 1.000 0.523

211


ID38 1.000 0.590

ID39 1.000 0.665

ID40 1.000 0.551

ID41 1.000 0.681

ID42 1.000 0.718

ID43 1.000 0.486

Extraction Method: Principal Component

Analysis.

Table 4.31 shows that out of remaining variables considered for factor analysis, the

communalities of seven variables are low (i.e. less than 0.5). These variables with their

respective communalities are: ID5 (Insider‘s information), 0.450; ID13 (coverage in the

press), 0.457; ID14 (recent price movements in a firm‘s stock/NAV), 0.469; ID18

(reputation of a company in the domestic market), 0.476; ID23 (publication in the

financial press, newspapers and electronic media), 0.441; ID25 (studying the portfolio

investments of other market players), 0.391; ID27 (economic forecasts by research

institutions), 0.489; and ID43 (ease in liquidity), 0.486. These seven variables are

removed from the rest of the variables. Further analysis is done with remaining 29

variables. An anti-image correlation matrix derived and new communalities are found for

these 29 variables influencing investment decision of investors, which is presented in

Table 4.32 and Table 4.33 respectively.

Table 4.32 indicates that all the variables have MSA value more than 0.5. Hence,



212

Table 4.32 Anti Image Correlation Matrix (for 29 variables) ID1 ID3 ID4 ID6 ID7 ID8 ID9 ID10 ID11 ID12 ID15 ID17 ID21 ID22 ID24 ID25 ID29 ID30 ID31 ID32 ID33 ID34 ID35 ID36 ID38 ID39 ID40 ID41 ID42

ID1 0.753 -0.339 -0.144 -0.030 -0.039 0.042 0.189 -0.056 -0.076 -0.022 -0.167 0.199 -0.219 0.022 -0.088 -0.169 0.003 -0.085 -0.054 -0.037 -0.061 -0.134 -0.017 -0.097 0.015 0.021 0.051 0.052 -0.082

ID3 -0.339 0.719 -0.025 0.014 0.013 -0.039 0.042 0.072 -0.227 0.057 0.062 -0.040 -0.006 0.058 0.091 -0.323 0.015 -0.115 0.141 -0.030 -0.188 -0.125 -0.001 0.016 -0.058 -0.035 0.010 0.011 0.055

ID4 -0.144 -0.025 0.620 0.067 0.069 -0.002 -0.009 -0.228 -0.064 -0.215 -0.214 -0.015 0.117 0.043 -0.087 -0.058 -0.060 -0.066 0.182 0.017 0.036 -0.124 0.059 -0.141 0.064 -0.071 0.008 -0.101 0.065

ID6 -0.030 0.014 0.067 0.751 -0.315 -0.108 -0.053 0.099 0.029 0.049 0.112 -0.108 0.012 0.114 0.061 -0.085 -0.035 -0.087 0.160 -0.070 -0.007 0.114 -0.168 0.076 0.016 -0.044 -0.131 -0.045 -0.024

ID7 -0.039 0.013 0.069 -0.315 0.739 0.045 0.035 -0.079 -0.168 0.112 0.038 0.068 -0.141 -0.020 0.045 -0.018 0.046 -0.095 0.036 -0.285 -0.039 -0.004 -0.041 -0.015 0.026 -0.145 -0.005 0.016 0.015

ID8 0.042 -0.039 -0.002 -0.108 0.045 0.581 0.150 -0.048 0.090 0.045 -0.173 -0.146 0.062 -0.034 -0.181 -0.091 -0.077 -0.063 -0.007 0.177 0.051 -0.129 0.022 -0.110 0.147 -0.050 0.068 -0.037 0.055

ID9 0.189 0.042 -0.009 -0.053 0.035 0.150 0.571 -0.274 -0.201 -0.204 -0.250 0.169 0.080 0.016 -0.031 -0.023 0.041 -0.011 0.008 0.077 -0.137 -0.184 -0.009 -0.101 0.173 -0.022 -0.022 0.081 0.053

ID10 -0.056 0.072 -0.228 0.099 -0.079 -0.048 -0.274 0.501 0.073 0.098 0.209 -0.165 -0.121 0.047 -0.106 0.017 0.142 -0.137 -0.064 0.060 -0.163 -0.019 -0.057 0.180 0.072 0.006 -0.008 0.066 -0.145

ID11 -0.076 -0.227 -0.064 0.029 -0.168 0.090 -0.201 0.073 0.528 -0.302 -0.007 -0.220 0.046 -0.129 -0.004 0.040 -0.059 0.085 -0.184 0.357 0.304 0.060 0.074 0.049 0.006 0.024 0.013 0.066 -0.084

ID12 -0.022 0.057 -0.215 0.049 0.112 0.045 -0.204 0.098 -0.302 0.578 0.057 -0.196 -0.069 0.145 0.048 0.007 -0.090 -0.035 -0.043 -0.312 0.016 0.232 -0.035 -0.056 0.020 -0.017 0.053 -0.090 0.052

ID15 -0.167 0.062 -0.214 0.112 0.038 -0.173 -0.250 0.209 -0.007 0.057 0.539 -0.301 -0.161 -0.053 -0.088 0.186 -0.014 -0.002 0.029 -0.014 -0.049 0.121 -0.079 0.082 -0.034 0.047 0.002 -0.026 -0.039

ID17 0.199 -0.040 -0.015 -0.108 0.068 -0.146 0.169 -0.165 -0.220 -0.196 -0.301 0.584 -0.161 -0.088 0.159 0.084 0.155 -0.025 -0.058 -0.180 -0.040 -0.056 0.038 0.103 -0.084 -0.070 -0.065 0.067 -0.002

ID21 -0.219 -0.006 0.117 0.012 -0.141 0.062 0.080 -0.121 0.046 -0.069 -0.161 -0.161 0.614 -0.097 0.040 -0.165 0.043 0.089 -0.032 0.119 0.057 0.045 0.015 -0.178 -0.008 0.025 -0.003 -0.065 0.136

ID22 0.022 0.058 0.043 0.114 -0.020 -0.034 0.016 0.047 -0.129 0.145 -0.053 -0.088 -0.097 0.734 -0.095 0.005 -0.062 -0.029 0.044 -0.154 -0.204 -0.045 -0.056 -0.074 -0.013 -0.015 0.046 -0.078 -0.110

ID24 -0.088 0.091 -0.087 0.061 0.045 -0.181 -0.031 -0.106 -0.004 0.048 -0.088 0.159 0.040 -0.095 0.626 -0.137 0.061 -0.103 0.073 -0.192 -0.022 0.159 -0.053 -0.039 -0.004 -0.061 0.014 0.039 -0.020

ID25 -0.169 -0.323 -0.058 -0.085 -0.018 -0.091 -0.023 0.017 0.040 0.007 0.186 0.084 -0.165 0.005 -0.137 0.763 0.017 0.169 -0.194 -0.126 -0.037 0.044 0.062 -0.014 -0.135 0.018 0.004 0.039 -0.087

ID29 0.003 0.015 -0.060 -0.035 0.046 -0.077 0.041 0.142 -0.059 -0.090 -0.014 0.155 0.043 -0.062 0.061 0.017 0.565 -0.314 -0.099 0.031 -0.172 0.030 0.070 -0.022 -0.063 -0.057 0.035 0.038 -0.073

ID30 -0.085 -0.115 -0.066 -0.087 -0.095 -0.063 -0.011 -0.137 0.085 -0.035 -0.002 -0.025 0.089 -0.029 -0.103 0.169 -0.314 0.494 -0.370 0.104 0.155 0.038 -0.095 -0.017 -0.030 0.142 -0.072 -0.035 0.077

ID31 -0.054 0.141 0.182 0.160 0.036 -0.007 0.008 -0.064 -0.184 -0.043 0.029 -0.058 -0.032 0.044 0.073 -0.194 -0.099 -0.370 0.546 -0.150 -0.125 -0.119 -0.013 -0.051 0.028 -0.049 0.025 -0.015 0.013

ID32 -0.037 -0.030 0.017 -0.070 -0.285 0.177 0.077 0.060 0.357 -0.312 -0.014 -0.180 0.119 -0.154 -0.192 -0.126 0.031 0.104 -0.150 0.546 -0.008 -0.095 0.055 0.058 -0.077 0.042 0.007 -0.012 0.013

ID33 -0.061 -0.188 0.036 -0.007 -0.039 0.051 -0.137 -0.163 0.304 0.016 -0.049 -0.040 0.057 -0.204 -0.022 -0.037 -0.172 0.155 -0.125 -0.008 0.582 0.048 -0.033 -0.009 -0.042 0.035 0.026 -0.036 0.096

ID34 -0.134 -0.125 -0.124 0.114 -0.004 -0.129 -0.184 -0.019 0.060 0.232 0.121 -0.056 0.045 -0.045 0.159 0.044 0.030 0.038 -0.119 -0.095 0.048 0.592 -0.009 0.044 -0.361 -0.036 0.008 -0.025 0.022

ID35 -0.017 -0.001 0.059 -0.168 -0.041 0.022 -0.009 -0.057 0.074 -0.035 -0.079 0.038 0.015 -0.056 -0.053 0.062 0.070 -0.095 -0.013 0.055 -0.033 -0.009 0.820 -0.077 -0.060 -0.481 0.028 -0.068 -0.043

ID36 -0.097 0.016 -0.141 0.076 -0.015 -0.110 -0.101 0.180 0.049 -0.056 0.082 0.103 -0.178 -0.074 -0.039 -0.014 -0.022 -0.017 -0.051 0.058 -0.009 0.044 -0.077 0.753 -0.084 -0.006 -0.185 0.041 -0.148

ID38 0.015 -0.058 0.064 0.016 0.026 0.147 0.173 0.072 0.006 0.020 -0.034 -0.084 -0.008 -0.013 -0.004 -0.135 -0.063 -0.030 0.028 -0.077 -0.042 -0.361 -0.060 -0.084 0.730 0.021 -0.093 0.061 0.021

ID39 0.021 -0.035 -0.071 -0.044 -0.145 -0.050 -0.022 0.006 0.024 -0.017 0.047 -0.070 0.025 -0.015 -0.061 0.018 -0.057 0.142 -0.049 0.042 0.035 -0.036 -0.481 -0.006 0.021 0.822 -0.031 -0.178 -0.219

ID40 0.051 0.010 0.008 -0.131 -0.005 0.068 -0.022 -0.008 0.013 0.053 0.002 -0.065 -0.003 0.046 0.014 0.004 0.035 -0.072 0.025 0.007 0.026 0.008 0.028 -0.185 -0.093 -0.031 0.862 -0.220 -0.215

ID41 0.052 0.011 -0.101 -0.045 0.016 -0.037 0.081 0.066 0.066 -0.090 -0.026 0.067 -0.065 -0.078 0.039 0.039 0.038 -0.035 -0.015 -0.012 -0.036 -0.025 -0.068 0.041 0.061 -0.178 -0.220 0.832 -0.434

ID42 -0.082 0.055 0.065 -0.024 0.015 0.055 0.053 -0.145 -0.084 0.052 -0.039 -0.002 0.136 -0.110 -0.020 -0.087 -0.073 0.077 0.013 0.013 0.096 0.022 -0.043 -0.148 0.021 -0.219 -0.215 -0.434 0.810

Measures of Sampling Adequacy (MSA)

213



ID1 1.000 0.698

ID3 1.000 0.645

ID4 1.000 0.518

ID6 1.000 0.628

ID7 1.000 0.612

ID8 1.000 0.684

ID9 1.000 0.600

ID10 1.000 0.720

ID11 1.000 0.654

ID12 1.000 0.696

ID15 1.000 0.617

ID17 1.000 0.763

ID21 1.000 0.524

ID22 1.000 0.573

ID24 1.000 0.574

ID28 1.000 0.650

ID29 1.000 0.612

ID30 1.000 0.690

ID31 1.000 0.573

ID32 1.000 0.680

ID33 1.000 0.517

ID34 1.000 0.700

ID35 1.000 0.588

ID36 1.000 0.505

ID38 1.000 0.586

ID39 1.000 0.684

ID40 1.000 0.526

ID41 1.000 0.683

ID42 1.000 0.720

Extraction Method: Principal Component

Analysis.

214

A close look at revised communalities as presented in Table 4.33 shows that for all the

variables extracted communalities are high (greater than 0.5), and hence, acceptable for

all variables to proceed for factor analysis.


Following the earlier explanation given in previous factor analysis performed for factors

preferred by respondents as source of information, an analysis of the Eigen values is

required. Eigen value represents the total variance explained by each factor (Malhotra,

2008354

). Eigen value depicts explanatory power of each factor. So, the factor which is

having higher Eigen value should be selected first. Table 4.34 shows the Eigen values of

all the variables that can be extracted. From Table 4.34, it can be seen that total 9 factors

have been identified at the end of the factor analysis with more than 1.0 Eigen value and

62.11 % of explained variance. Following this, total 9 factors are extracted for this study.

Rotation sums of squared loadings are used for analysis. Table 4.35 presents the

component matrix.


Education, p. 561.

215

Table 4.34 Total Variance Explained

Com

pone

nt

Initial Eigenvalues

Extraction Sums of

Squared Loadings

Rotation Sums of Squared

Loadings

Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% Total % of

Variance Cumulative

%

1 4.173 14.391 14.391 4.173 14.391 14.391 3.649 12.583 12.583

2 2.988 10.305 24.696 2.988 10.305 24.696 2.644 9.119 21.702

3 2.491 8.590 33.286 2.491 8.590 33.286 1.908 6.578 28.280

4 1.641 5.658 38.944 1.641 5.658 38.944 1.782 6.145 34.425

5 1.540 5.312 44.255 1.540 5.312 44.255 1.772 6.110 40.535

6 1.431 4.934 49.189 1.431 4.934 49.189 1.716 5.919 46.454

7 1.325 4.567 53.756 1.325 4.567 53.756 1.614 5.567 52.021

8 1.251 4.313 58.069 1.251 4.313 58.069 1.553 5.354 57.374

9 1.172 4.040 62.109 1.172 4.040 62.109 1.373 4.735 62.109

10 0.998 3.444 65.553

11 0.946 3.265 68.818

12 0.838 2.890 71.708

13 0.807 2.782 74.490

14 0.760 2.621 77.111

15 0.720 2.482 79.593

16 0.673 2.322 81.915

17 0.634 2.185 84.100

18 0.581 2.003 86.103

19 0.515 1.777 87.880

20 0.466 1.608 89.488

21 0.444 1.531 91.019

22 0.432 1.491 92.510

23 0.417 1.436 93.947

24 0.386 1.330 95.277

25 0.317 1.093 96.370

26 0.289 0.997 97.367

27 0.268 0.926 98.293

28 0.255 0.878 99.171

29 0.240 0.829 100.000


216


To extract the factors, principal component analysis method is used, as it considers the

total variance in the data and derives the factors that contain small proportions of unique

variance and in some instances, error variance. Table 4.35 shows component matrix (un-

rotated factor matrix).

Table 4.35 Component Matrixa

Variables Component

1 2 3 4 5 6 7 8 9

ID39 0.723 -0.383 -0.020 0.020 0.011 0.007 -0.038 0.104 0.044

ID42 0.713 -0.398 -0.011 -0.036 -0.064 -0.131 0.001 0.143 -0.101

ID41 0.684 -0.427 -0.022 -0.007 -0.052 -0.082 0.065 0.095 -0.099

ID35 0.672 -0.332 -0.037 -0.042 0.039 0.092 -0.035 0.065 0.085

ID40 0.576 -0.335 -0.072 0.040 -0.163 -0.103 0.032 0.181 -0.066

ID7 0.514 0.076 -0.147 0.272 -0.092 0.305 -0.280 -0.161 0.201

ID6 0.489 -0.170 -0.258 0.194 -0.169 0.184 -0.206 -0.237 0.307

ID36 0.472 -0.007 0.185 -0.159 -0.096 -0.367 0.010 -0.030 -0.262

ID22 0.411 0.030 0.101 -0.007 0.233 0.134 0.386 -0.035 -0.265

ID3 0.272 0.642 0.200 0.084 -0.076 -0.238 -0.153 0.057 0.149

ID28 0.397 0.629 0.034 0.067 0.021 -0.143 -0.248 -0.090 -0.035

ID1 0.410 0.572 0.302 -0.019 0.024 -0.260 -0.178 -0.079 0.070

ID38 0.280 0.505 -0.107 0.124 -0.135 -0.014 0.327 0.305 -0.087

ID33 0.207 0.368 -0.013 -0.186 0.365 0.336 0.013 0.049 -0.235

ID4 0.090 -0.074 0.598 -0.085 0.228 -0.233 -0.137 0.108 -0.052

ID11 -0.173 -0.134 0.594 0.272 -0.344 -0.162 -0.135 0.098 0.082

ID12 -0.121 -0.182 0.592 0.323 -0.206 0.111 -0.159 -0.126 -0.311

ID15 -0.010 -0.221 0.532 0.145 0.311 -0.060 0.376 -0.145 0.017

ID9 -0.254 -0.283 0.400 -0.073 0.181 0.158 -0.334 0.323 -0.129

ID17 0.007 -0.128 0.404 0.549 0.075 0.272 0.389 0.038 0.222

ID29 0.105 0.090 0.272 -0.478 -0.437 0.137 0.166 -0.174 -0.152

ID30 0.127 0.050 0.390 -0.460 -0.365 0.331 0.031 -0.098 0.235

ID21 0.238 0.300 0.243 0.370 0.115 -0.152 0.009 -0.176 0.123

217

ID24 0.285 0.023 0.150 -0.302 0.442 -0.008 -0.146 -0.375 -0.145

ID10 0.079 -0.066 0.248 -0.166 0.435 0.333 -0.353 0.340 0.284

ID32 0.321 0.332 -0.089 0.322 0.105 0.442 0.015 -0.186 -0.339

ID31 0.130 0.286 0.362 -0.188 -0.342 0.424 0.062 0.079 -0.020

ID34 0.199 0.465 -0.023 -0.053 0.042 0.002 0.238 0.596 0.166

ID8 0.168 -0.050 0.175 -0.295 0.215 -0.131 0.346 -0.299 0.513


a. 9 components extracted.

To extract the factors and to name them, an analysis of factors loadings in the rotated

factor matrix is used in present factor analysis. The interpretation of factors is done by

identifying the variables that have very high loadings on the same component.

For better reduction of variables, factor loadings more than or/and equal to 0.40 were

considered under each factor. Fortunately, all the variables got the factor loading greater

than 0.40. Total nine factors have been extracted. Finally, all the variables are grouped

under the 9 factors. Naming of factors is carried out based on Table 4.36.

The factors extracted, their respective items with the assigned codes and their

corresponding factor loading are given in Table 4.37.

218

Table 4.36 Rotated Component Matrix

Variables Component

1 2 3 4 5 6 7 8 9

ID42 0.848 0.024 -0.015 0.000 0.019 0.015 -0.007 0.004 -0.001

ID41 0.821 -0.037 0.042 -0.001 0.050 0.040 -0.023 -0.035 0.019

ID39 0.793 0.018 0.044 -0.014 0.054 0.188 -0.007 0.100 0.069

ID40 0.709 -0.020 -0.013 -0.005 -0.060 0.064 0.087 -0.062 -0.059

ID35 0.701 -0.007 0.016 0.037 0.108 0.228 -0.010 0.129 0.122

ID36 0.487 0.342 -0.069 0.115 0.037 -0.297 -0.098 -0.153 -0.021

ID1 0.065 0.812 -0.015 0.131 0.080 -0.027 0.059 0.032 0.076

ID3 -0.065 0.755 -0.032 0.082 -0.036 0.041 0.244 0.001 0.010

ID28 0.013 0.740 -0.159 0.018 0.206 0.140 0.093 -0.052 -0.062

ID21 -0.001 0.516 0.345 -0.124 0.036 0.121 -0.005 -0.072 0.048

ID17 -0.013 -0.092 0.834 -0.009 -0.030 0.165 0.164 0.053 0.006

ID15 0.057 -0.023 0.658 -0.015 0.076 -0.302 -0.174 0.067 0.219

ID11 -0.028 0.159 0.552 0.190 0.006 -0.141 -0.102 0.125 -0.275

ID12 -0.015 0.058 0.475 0.216 -0.142 -0.106 -0.359 0.076 -0.403

ID30 0.029 0.022 0.014 0.786 -0.073 0.083 -0.028 0.146 0.190

ID29 0.064 0.015 -0.089 0.727 0.046 -0.168 -0.077 -0.187 0.027

ID31 -0.050 0.121 0.108 0.675 0.114 0.082 0.195 0.094 -0.144

ID33 -0.054 0.146 -0.092 0.088 0.650 -0.005 0.130 0.191 -0.013

ID32 0.012 0.186 0.161 0.018 0.608 0.354 0.033 -0.144 -0.321

ID22 0.314 0.032 0.257 0.063 0.511 -0.123 0.093 -0.115 0.071

ID24 0.141 0.233 -0.073 0.024 0.444 -0.107 -0.442 0.162 0.249

ID7 0.273 0.238 0.012 0.027 0.112 0.678 -0.027 0.039 -0.068

ID6 0.380 0.058 -0.043 -0.008 -0.059 0.669 -0.117 -0.069 0.091

ID4 0.151 0.289 0.242 0.055 -0.074 -0.408 -0.181 0.381 0.016

ID34 0.026 0.234 -0.043 0.040 0.099 -0.088 0.772 0.140 0.084

ID38 0.063 0.285 0.019 0.058 0.204 -0.011 0.618 -0.254 -0.090

ID10 0.033 0.005 0.015 0.014 0.113 0.103 0.057 0.824 0.114

ID9 -0.042 -0.179 0.097 0.042 -0.095 -0.249 -0.153 0.619 -0.281

ID8 0.070 0.076 0.188 0.136 -0.011 -0.029 -0.081 -0.009 0.782

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 14 iterations.

219

Table 4.37 Composition of Each Factor Identified in Factor Analysis

Factor Items Factor

loadings

Factor 1

Personal Financial

Need

Affordable minimum investment amount (ID42) 0.848

Safety associated with investment (ID41) 0.821

Ease of obtaining borrowed fund (ID39) 0.793

Preferred investment time horizon (ID40) 0.709

Liquidity associated with investment (ID35) 0.701

Availing the benefit of income tax deduction (ID36) 0.487

Factor 2

Accounting, Business

& Financial

Information

Condition of financial statement (ID1) 0.812

Past performance of the firm (ID3) 0.755

Study of Annual Reports (ID28) 0.740

Market capitalization of company (ID21) 0.516

Factor 3

Economic &

Regulatory

Environment

Current economic indicators (ID17) 0.834

Statements from politicians and governmental officials (ID15) 0.658

Political party affiliation (ID11) 0.552

Contribution of a firm towards social causes (ID12) 0.475

Factor 4

Operational

Feedback

Opinions from friends and relatives (ID30) 0.786

Opinions from family members (ID29) 0.727

Opinions from existing investors (ID31) 0.675

Factor 5

Advocate

Recommendation

Opinion of credit rating agencies‘ reports (ID33) 0.650

Financial advisors/Broker and analyst‘s recommendation (ID31) 0.608

Conversation/exchanges of views with professional colleagues

(ID22) 0.511

Conversation/exchanges of views with company executives and

sector experts (ID24) 0.444

Factor 6

Overall Group

Performance

Result of technical analysis (ID7)) 0.678

Result of fundamental analysis (ID6) 0.669

Company‘s position in the industry (ID4) -0.408

Factor7

Credit features

Diversification needs (ID34) 0.772

Minimizing risk (ID38) 0.618

Factor 8

Personal Inclination

Perceived ethics of company(ID10) 0.824

Feeling for a company‘s products and services (ID9) 0.619

Factor9

Monetary Expectation

0.782 Expected return on investment (ID8)

220

4.9.2.7 Naming of factors

According to the loading of variables on these nine factors, they can be explained as:

Factor 1: Personal Financial Need

Total six variables were identified under factor 1 are ‗availing the affordable minimum

investment amount‘ (0.848), ‗safety associated with investment‘ (0.821), ‗ease of

obtaining borrowed fund‘ (0.793), ‗preferred investment time horizon‘ (0.709), ‗liquidity

associated with investment‘ (0.701) and ‗availing the benefit of income tax deduction‘

(0.487). These variables are grouped under ―Personal Financial Need”, as these

variables reflect each individual investor‘s needs as to what is safety, liquidity, time

horizon and tax benefit according to his/her personal and/or unique circumstances. Every

individual investor looks at variables from his/her own point of view, which would be

differing from investor to investor. This extracted factor explains 12.58 % of variance,

which is the highest among all the factors.


), Hussein et al. (2009356

) examined that personal financial

needs of an individual investor mostly influence the investment decision. Nagy and

Obenberger (1994357

) also added that ―perhaps sophisticated investors view investment

capital and consumption expenditures independent entities‖ (p. 67).

Factor 2: Accounting, Business and Financial Information

The four variables were identified under factor 2 are ‗condition of financial statement‘

(0.812), ‗past performance of the firm‘ (0.755), ‗study of annual reports‘ (0.740), and

‗market capitalization of company‘ (0.516). The group of these variables is named as

355 Nagy, R. A. & Obenberger, R. W. (1994). Factors affecting investors behaviour. Financial Analyst

Journal, 50, 63-68. 356 Hussein A. H. Al- Tamini & Al Anood Bin Kali (2009). Financial literacy and investment decision of

UAE investors. The Journal of Risk Finance, 10 (5), Emerald Group Publishing limited, p. 508 357 Nagy, R. A. &Obenberger, R. W. (1994). Factors affecting investors‘ behaviour. Financial Analyst

Journal, 50, 63-68.

221

“Accounting, Business and Financial Information”, as these variables are related with

an individual firm‘s accounting, business and financial performance. This extracted factor

explains 9.12 % of variance.


) said that ―accounting, business and financial information of the

firms and their past performance also has its bearing to the individual investors to some

extent, and the individuals strongly rely on this while investing. However, these are said

to be the part of informational sources. This study also added that majority of the

investors surveyed do not consider financial statements, as individual investors facing

complexity of interpreting the financial statements‖ (p.22).

Factor 3: Economic and Regulatory Environment

The four variables identified under factor 3 are ‗current economic indicators‘ (0.834),

‗statement from politicians and government officials‘ (0.658), ‗political party affiliation‘

(0.552), and ‗contribution of a firm towards social causes‘ (0.475). These variables are

grouped under “Economic and Regulatory Environment”, as these variables seek to

examine the firm‘s presence of business in the context of the economic, regulatory and

social environment under which the firm operates. This extracted factor explains 6.58 %

of variance.

Aregbeyan and Mbadiugha (2011359

) explained that along with the social, psychological

factors, and cultural factors, investors always rely on economic factors and their

investment decisions are always influences by these economic factors. Hussein et al.

(2009360

) also suggested that statement from government officials and current economic

indicators do have their influence on investment decision of individual investors.

358


transformation approach. Munich Personal RePEc Archive No. 29722, accessed on April 15, 2011 at http://mpra.ub.uni-muenchen.de/29722/ 359 Aregbeyen, O. &Mbadiugha, O. S. (2011). Factors influencing investors decisions in shares of quoted

companies in Nigeria. The Social Sciences, 6 (3), p.1. 360 Hussein A. H. Al- Tamini & Al Anood Bin Kali (2009). Financial literacy and investment decision of

UAE investors. The Journal of Risk Finance, 10 (5), Emerald Group Publishing limited, 508


222

Blumberg et al. (1997361

) added that the stakeholders are always interested to the extent

to which the company is investing in social and related issues. They always want to see

company as a going concern.

Factor 4: Operational Feedback

Total three variables identified under factor 4 are ‗opinions from friends and relatives‘

(0.786), ‗opinions from family members‘ (0.727) and ‗opinions from existing investors‘

(0.675). The group of these variables is named as “Operational Feedback”. The

investor generally gets this some operational feedback from their family members,

friends and existing investors, which may support their individual investor‘s views

towards investment alternative and/or firm‘ operation to make investment decision. This

factor seeks to give insider‘s view of the firm who have either an interest in the company

or have done some analysis of the company. This extracted factor explains 6.15 % of

variance.


) has stated the group of these variables as informational

asymmetry. This study further added that set of variables explaining this component leads

to infer that individual investors are suffered from information inferiority complex. They

tend to rely heavily on the easily available and accessible information. They are

influenced by the information hovering around them and which can be easily used by

investors for their decisions; rather they don‘t tend to check the reliability of this

information (as operational feedback) and prefer to those piece of information which are

easy to incorporate into their decisions. Instead of incorporating all the publically

available information as suggested by the standard definition of efficient market theory,

investors tend to discount the information that seems complex to incorporate into their

decisions-making process, and adopt only those information, which are easily available

361 Blumberg, J., Korswold, A. & Blum, G. (1996). Environmental Performance and Shareholder Value

World Business Council for Sustainable Development Geneva. 362





223

and adjustable in nature. These are the operational feedbacks easily available from family

members, friends and relative and existing investors.

Factor 5: Advocate Recommendation

There are four variables identified under factor 5. These variables are ‗rating agencies‘

reports‘ (0.650), ‗financial advisors/brokers and analyst‘s recommendation‘ (0.608),

‗conversation/ exchanges of views with professional colleagues‘ (0.511) and

‗conversation/exchanges of views with company executives and sector experts‘ (0.444).

These variables are grouped under “Advocate Recommendation”, as these variables are

related to the recommendations that the investor gets from company insiders, outsider

and professionals. This recommendation provides outside independent expert‘s views

about the firm‘s position and what they think about the firm and its prospect, which is

objective/neutral in nature and it is perceived to be unbiased. This extracted factor

explains 6.11 % of variance.


) said that ―advocate recommendation includes purchase

recommendations from brokerage houses, individual stock brokers and co-workers. This

study also added that these information sources could be constructed as a

recommendation from sources with vested interested in the investor‘s ultimate actions.

Although, many investors obviously rely on professional expertise‖ (p. 67).

Factor 6: Overall Group Performance

The three variables identified under factor 6 are ‗result of technical analysis‘ (0.678),

‗result of fundamental analysis‘ (0.669) and ‗company‘s position in the industry‘ (-

0.408). The group of these variables is named as “Overall Group Performance”, as

these variables impinge on firm‘s performance. This factor shows that while investing,

the individual investor do not rely only on company‘s position in the domestic market,

363 Nagy, R. A. & Obenberger, R. W. (1994). Factors affecting investor‘ behaviour. Financial Analyst

Journal, 50, 63-68.

224

but also give due importance to the technical analysis and to what extent the

company/firm is fundamentally strong. This extracted factor explains 5.92 % of variance.


) said that the group of these variables shows prudence and

precaution attitude. They also added that each variable included under this factor is

associated with different behavioural attitude. These variables underline the symmetric

behaviorual attitude of risk aversion. These behavioural factor traduces the prudent and

cautions attitude of individual investors. The study said that investors tend to use trend

analysis and their decision are always based on market share and reputation of the firm/

company (p. 21).

Factor 7: Credit Features

Two variables identified under factor 7 are ‗diversification need‘ (0.772) and ‗minimizing

risk‘ (0.618). These variables are grouped under “Credit Features”, as these variables

are associated with creditability of an investor. The investors‘ community often tries to

minimize their total risk associated with their whole investment portfolio through

diversification by studying the risk-return trade-off of various investment alternatives.


Hussein et al. (2009365

) suggested that diversification needs and minimizing the risk are

two important variables that heavily influence investment decision of investors. Nagy and

Obenberger (1994366

) also suggest that investors often look for the diversification need

while investing.

Factor 8: Personal Inclination

364 Chandra, A. & Kumar, R. (2011). Determinants of individual investor behaviour: An orthogonal linear


http://mpra.ub.uni-muenchen.de/29722/ 365

Hussein A. H. Al- Tamini & Al Anood Bin Kali (2009). Financial literacy and investment decision of

UAE investors. The Journal of Risk Finance, 10 (5), Emerald Group Publishing limited, 500-516. 366 Nagy, R. A. & Obenberger, R. W. (1994). Factors affecting investors‘ behaviour. Financial Analyst

Journal, 50, 63-68.


225

The two variables identified under factor 8 are ‗firm‘s perceived ethics of a company‘

(0.824) and ‗feelings for a company‘s products and services‘ (0.619). The group of these

variables is named as “Personal Inclination”, as these variables are related to the

individual investor‘s internal inclination towards the firm, its operation and business

practices. This inclination may be due to lack of widespread knowledgeable information

about a particular investment alternative, along with the resulting herd behavior, thus

contributing towards the relative neglect of consideration of significant traditional values.


Draft Green Paper on Consumer Policy Framework (DTI) (2004367

) states that more and

more consumers are interested in the world behind the products, the production process

and the ethics of the company that produces goods and services. Hussein et al. (2009368

)

and Nagy and Obenberger (1994369

) also suggested that the self image factor/ firm image

coincidence which consisting of variables such as ‗perceived ethics of firm‘ and ‗feeling

for firm‘s products and services‘ influence the investment decision of investors (p. 513).

Factor 9: Monetary Expectation

Only one variable was identified under factor 9 ‗expected return on investment‘ (0.782).

It is named as “Monetary Expectation” as while making investment decision, individual

always looks to collect the information about the pattern of profit distribution and starts

to expect the return to compensate the risk associated with investment. This extracted

factor explains 4.74 % of total variance.


) suggested that monetary expectation can be considered

as classic factor that focuses on wealth maximization criterion.

367 Government Gazette (2004). Draft Green Paper on Consumer Policy Framework. Republic of South

Africa, 471 (9), September 9, 2004, Pretoria. 368

Hussein A. H. Al- Tamini & Al Anood Bin Kali (2009). Financial literacy and investment decision of

UAE investors. The Journal of Risk Finance, 10 (5), Emerald Group Publishing limited, 500-516. 369

Nagy, R. A. & Obenberger, R. W. (1994). Factors affecting investors‘ behaviour. Financial Analyst

Journal, 50, 63-68. 370 Nagy, R. A. & Obenberger, R. W. (1994). Factors affecting investors‘ behaviour. Financial Analyst

Journal, 50, 63-68.

226

4.9.2.8 Mean score of extracted factors influencing investment decision

Table 4.38 represents the factor wise mean influencing score. The score is derived by

taking the grand mean value of variables clubbed in each factor. From Table 4.38, it is

found that for factor 7, the mean score is highest, i.e. 4.07. This indicates that the factor

named ‗credit features‘ is the most influencing factor on investment decision of investors.

This shows that investors continuously try to decrease the total risk associated with their

investment portfolio by diversifying their portfolio. This factor is followed by the mean

score 4.03 of factor 9, i.e. ‗Monetary Expectation‘, which shows that while diversifying

their total portfolio, investors do consider the monetary expectation by way of expected

return to compensate the risk associated with their portfolio. The third important factor

that influences investment decision is Factor 2: ‗Accounting, Business and Financial

Information‘, having a mean score of 3.98, which indicates that the investors rely and

emphasize on rational decision making criteria. This factor is followed by the factor 5

with mean score of 3.74; ―Advocate Recommendation‖. This shows that published and

non published information does have their influence investment decision. The least score

is for factor 1 i.e. Personal Financial Need having mean score of 3.02.

Table 4.38 Mean Score of Extracted Factors

Factor Factor Name Grand Mean

Value

Factor 1 Personal financial need 3.02

Factor 2 Accounting, business and financial information 3.98

Factor 3 Economic and regulatory environment 3.25

Factor 4 Operational feedback 3.66

Factor 5 Advocate recommendation 3.74

Factor 6 Overall group performance 3.24

Factor 7 Credit features 4.07

Factor 8 Personal inclination 3.70

Factor 9 Monetary expectation 4.03

Table 4.39 indicates the mean score of 29 variables from which 9 factors that influence

the investment decision of investors. From Table 4.39, it can be seen that the most

227

influencing variables on investment decision of investors is ‗rating agencies‘ reports‘

(4.17) (which shows that investors‘ investment decision is highly influenced by the

independent opinion given by the rating agencies) followed by the variable

‗diversification needs‘ (4.14) (this shows that investors look for the various investment

alternatives to spread/ to decrease their risk).

Table 4.39 Mean Score of Each Variable within Each Factor

Variables within each factor Mean

value

Factor 1: Personal financial need

Affordable minimum investment amount 2.77

Safety associated with investment 2.98

Ease of obtaining borrowed fund 3.03

Preferred investment time horizon 2.74

Liquidity associated with investment 2.91

Availing the benefit of income tax deduction 3.44

Grand mean value 3.02

Factor 2: Accounting, Business and Financial Information

Condition of financial statements 4.05

Past performance of the firm 3.98

Study of annual report 4.09

Market capitalization of a company 3.83


Factor 3: Economic and regulatory environment

Current economic indicators 3.26

Statements from politicians and Government officials 3.29

Contribution of firm towards social causes 3.22

Political party affiliation 3.20


Factor 4: Operational feedback

Friends and Relatives 3.73

Family members 3.58

Present Investors 3.67


Factor 5: Advocate recommendation

Rating agencies‘ report 4.17

Advisor/brokers/ analyst‘s recommendation 3.87

Conversation/exchanges of views with Professional colleagues 2.94

228

Conversations/exchanges of views with company executives and sector

experts 3.97


Factor 6: Overall group performance

Result of technical analysis 2.88

Result of fundamental analysis 2.94

Company‘s position in the industry 3.91


Factor 7: Credit features

Diversification needs 4.14

Minimizing risk 4.01


Factor 8: Personal inclination

Perceived ethics of a company 4.11

Feeling for company's products/services 3.29


Factor 9: Monetary expectation

Expected return on investment 4.03


5.10 Cross Tabulation and statistical tests

In this section, simultaneous analysis of two variables is carried out through cross

tabulation. Hypothesis testing is also included in this section.

Association between explainable variables and financial literacy level

First, to test the significant association between various explainable variables such as

investors‘ age, gender, education, income, stage of family life cycle, monthly income,

employment structure, workplace activity, number of years of work experience, number

of years of investment experience, risk tolerance level and number of times investors

shop around and financial literacy level, the Chi-Square test was performed. Chi-square


229

test enables to explain whether or not two attributes are associated. Kothari (2009371

)

suggested that ―Chi-square test can be used to determine if categorical data shows

dependency or the two classifications are independent. It can be also used to make

comparisons between theoretical populations and actual data when categories are used.

Thus, the chi-square test is applicable in large number of problems. The test is, in fact, a

technique through the use of which it is possible for all researchers to (i) test the

goodness of fit, (ii) test the significance of association between two attributes, and (iii)

test the homogeneity or the significance of population variance‖.

4.10.1 Association between investors‟ age and their financial literacy level

The data regarding investors‘ age and their financial literacy level is given in Table 4.40.

Table 4.40 Cross Tabulation of Investors‟ Age and their Financial Literacy Level

Financial

literacy level

Respondents‟ age Total

18 to 25 26 to 35 36 to 45 46 to 55 56 to 65

Low 85

(95.5)

65

(85.53)

35

(38.46)

16

(21.33)

27

(55.10)

228

(59.22)

High 4

(2.5)

11

(14.47)

61

(67.03)

59

(78.67)

22

(44.90)

157

(40.78)

Total 89

(100)

76

(100)

96

(100)

75

(100)

49

(100)

385

(100) Note: Figures in parenthesis shows the percentage of respondents

Hypotheses for the data shown in Table 4.40 for chi-square test are as under:

H0: There is no significant association between investors‘ age and their financial literacy

level.

H1: There is a significant association between investors‘ age and their financial literacy

level.

371 Kothari, C.R. (2009). Research Methodology: Methods and Techniques (2nd ed.). New Delhi: New Age

International Publishers, p. 233.

230

Table 4.41 Chi-Square Tests

Value df Sig.

Pearson Chi-Square 1.358 4 0.000

Likelihood Ratio 153.949 4 0.000

Linear-by-Linear Association 82.464 1 0.000

Number of Valid Cases 385

The test was performed at 5% level of significance. The output of Chi-square test is as

presented in Table 4.41. The Pearson Chi-square significance value is 0.000 with degree

of freedom 4. Therefore, null hypothesis is rejected and hence, it is found that there is a

significant association between investors‘ age and their financial literacy level. It might

be also concluded that investors‘ age and their financial literacy level are not independent

of each other. In other words, these two variables are significantly associated with each

other.

Chi-square test shows the statistical significance between the two variables. It does not

tell us the strength of association between two variables in the cross tabulation. To

measure the strength of this association, The Cramer‘s V, one of the measures of indexes

of agreement is used, which is shown in Table 4.42.

Table 4.42 Symmetric Measures

Value Sig.

Nominal by

Nominal

Phi 0.594 0.000

Cramer's V 0.594 0.000

Contingency Coefficient 0.511 0.000


From Table 4.42, it can be seen that the value of Cramer‘s V is significant with 0.000 and

the degree of association between these two variables is 59.4%.

231

4.10.2 Association between investors‟ gender and their financial literacy level

The data regarding the investors‘ gender and their financial literacy level is given in

Table 4.43.

Table 4.43 Cross Tabulation of Investors‟ Gender and their Financial Literacy

Level

Financial

literacy level

Respondents‟ gender

Total Male Female

Low 157

(51.48)

71

(88.75)

228

(59.22)

High 148

(48.52)

9

(11.25)

157

(40.78)

Total 305

(100)

80

(100)

385

(100)


Hypotheses for the data shown in Table 4.43 for chi-square test are as under.

H0: There is no significant association between investors‘ gender and their financial

literacy level.

H1: There is a significant association between investors‘ gender and their financial

literacy level.

Table 4.44 Chi-square tests

Value df Sig.


Continuity Correction 34.965 1 0.000




Cramer's V 0.308 0.000

Number of valid cases 385

232


presented in Table 4.44. The Pearson Chi-square significance value is 0.000 and degree

of freedom is 1. Therefore, null hypothesis is rejected and hence, it is found that there is a

significant association between investors‘ gender and their financial literacy level. It

might be also concluded that investors‘ gender and their financial literacy level are not

independent of each other. In other words, these two variables are significantly

associated. From the last row of the same table, it is also seen that Cramer‘s V value is

significant with 0.000 and the degree of association between these two variables is

30.8%.

4.10.3 Association between investors‟ education and their financial literacy level

The data regarding investors‘ education their financial literacy level is given in Table

4.45.

Table 4.45 Cross Tabulation of Investors‟ Education and their Financial Literacy

Level

Financial

literacy

level

Respondents‟ education

Total

Primary Secondary

Higher

secondary Diploma Graduation

Post-

graduation

Low 18

(75)

22

(48.89)

30

(65.22)

18

(62.07)

65

(52.42)

75

(61.48)

228

(59.22)

High 6

(25)

23

(51.11)

16

(34.78)

11

(37.93)

54

(45.38)

47

(38.52)

157

(40.78)

Total 24

(100)

45

(100)

46

(100)

29

(100)

119

(100)

122

(100)

385

(100)



H0: There is no significant association between investors‘ education and their financial

literacy level.

233

H1: There is a significant association between investors‘ education and their financial

literacy level.


Value df Sig.






presented in Table 4.46. From the table, it can be seen that the Pearson Chi-square

significance value is 0.257 and degree of freedom is 5. Therefore, null hypothesis is not

rejected and hence, it is found that there is no significant association between the

investors‘ education and their financial literacy level. It might be also concluded that

investors‘ education and their financial literacy level are independent of each other. In

other words, these two variables are not significantly associated.

4.10.4 Association between investors‟ monthly income and their financial literacy

level

The data regarding the investors‘ monthly income and their financial literacy level is

given in Table 4.47.

234

Table 4.47 Cross Tabulation of Investors‟ Monthly Income and their Financial

Literacy Level

Financial

literacy

level

Respondents‟ monthly income

Upt0 Rs.

10,000

Rs. 10,001 to

Rs. 15,000

Rs. 15,001 to

Rs, 20,000

Rs. 20,001 to

Rs. 25,000

Rs. 25,001

and above

Total

Low 80

(84.21)

62

(72.94)

51

(61.45)

25

(32.05)

10

(22.73)

228

(59.22)

High 15

(15.79)

23

(27.06)

32

(38.56)

53

(67.95)

34

(77.27)

157

(40.78)

Total 95

(100)

85

(100)

83

(100)

78

(100)

44

(100)

385

(100)



H0: There is no significant association between the investors‘ monthly income and their


H1: There is a significant association between the investors‘ monthly income and their



Value Df Sig.




Cramer‘s V 0.304 0.000


The Chi-square test was performed at 5% level of significance. The output of Chi-square

test is as presented in Table 4.48. The Pearson Chi-square significance value is 0.000 and

degree of freedom is 4. Therefore, null hypothesis is rejected and hence, it is found that

there is a significant association between the investors‘ monthly income and their

financial literacy level. It might be also concluded that investors‘ monthly income and

235

their financial literacy level are not independent of each other. In other words, these two

variables are significantly associated. From the last row of the same table, it is also seen

that Cramer‘s V value is significant with 0.000 and the degree of association between

these two variables is 30.4%.

4.10.5 Association between investors‟ stage in family life cycle and their financial

literacy level

The data regarding investors‘ stage in family life cycle and their financial literacy level is


Table 4.49 Cross Tabulation of Investors‟ Stage in Family Life Cycle their Financial

Literacy Level

Financial

literacy

level

Respondents‟ stage in family life cycle Total

Young

single

Young

married

without

children

Young

married

with

children

Middle

age

married

with

children

Middle age

married

without

dependent

children

Older

married

Low 56

(83.58)

48

(71.64)

55

(57.89)

44

(43.56)

16

(48.48)

9

(40.91)

228

(59.22)

High 11

(16.42)

19

(20.36)

40

(42.11)

57

(56.44)

17

(51.51)

13

(59.09)

157

(40.78)

Total 67

(100)

67

(100)

95

(100)

101

(100)

33

(100)

22

(100)

385

(100)



H0: There is no significant association between investors‘ stage in family life cycle and


H1: There is a significant association between investors‘ stage in family life cycle and


236


Value df Sig.




Cramer‘s V 0.304 0.000





there is a significant association between the investors‘ stage in family life cycle and their

financial literacy level. It might be also concluded that investors‘ stage in family life and

their financial literacy level are not independent of each other. In other words, these two

variables are significantly related. From the last row of the same table, it is also seen that

Cramer‘s V value is significant with 0.000 and the degree of association between these

two variables is 30.4%.

4.10.6 Association between investors‟ employment structure and their financial

literacy level

The data regarding investors‘ employment structure and their financial literacy level is


Table 4.51 Cross Tabulation of Investors‟ Employment Structure and Financial

Literacy Level

Financial

literacy

level

Full

time

salaried

Part

time

salaried Casual

Self

Employed

House

wife Retired

Un-

employed Other Total

Low 134 29 7 41 8 6 1 2 228

High 94 13 3 26 6 14 1 0 157

Total 228 42 10 67 14 20 2 2 385

237

To check the association between these two variables statistically, Chi-square test is

performed. Although, there are no assumptions made as to the shape of data distribution

for this non parametric technique, there are restrictions on its applications. As a rule of

thumb, if the degree of freedom is greater than one, not more than 20% of the cells

should have expected frequencies of less than 5. If this requirement can‘t be met,

researcher should attempt to combine cells, until it conforms to this rule, but only if the

combination would not render the data meaningless (Luck and Rubin, 2003372

). Based on

this rule, for the data in the above table, not more than 2 cells should have expected

frequency less than 5. But, for this data exactly cells have expected frequency less than

5, as indicted in the Table 4.51. Hence regrouping is not done by combining. The new

revised table free from this limitation is as shown below (see Table 4.52).

Table 4.52 Revised Cross Tabulation of Investors‟ Employment Structure and their

Financial Literacy Level

Financial

literacy

level

Respondents‟ employment structure Total

Full time

salaried

Part

time

salaried Casual

Self

Employed Housewife

Retired,

Unemployed

and others

Low 134

(58.77)

29

(69.05)

7

(70.00)

41

(61.19)

8

(51.14)

9

(37.50)

228

(59.48)

High 94

(41.23)

13

(30.95)

3

(30.00)

26

(38.81)

6

(42.85)

15

(62.50)

157

(40.78)

Total 228

(100)

42

(100)

10

(100)

67

(100)

14

(100)

24

(100)

385

(100)



H0: There is no significant association between investors‘ employment structure and their


372 Luck, D. &Rubin, D. (2003). Marketing Research (7th ed.). New Delhi: Prentice Hall of India Pvt. Ltd.

p. 347

238

H1: There is a significant association between investors‘ employment structure and their



Value Df Sig.







degree of freedom is 4. Therefore, null hypothesis is not rejected and hence, it is found

that there is no significant association between investors‘ employment structure and their

financial literacy level. It might be also concluded that investors‘ employment structure

and their financial literacy level are independent of each other. In other words, these two

variables are not significantly associated.

4.10.7 Association between investors‟ type of workplace activity and their financial

literacy level

The data regarding investors‘ type of workplace activity and their financial literacy level

is given in Table 4.54.

239

Table 4.54 Cross Tabulation of Investors‟ Type of Workplace Activity and their


Financial

literacy

level

Respondents‟ type of workplace activity

Finance

related work

place activity

Non finance

related work

place activity

Other Total

Low 37

(27.82)

182

(75.21)

9

(90.00) 228

(59.22)

High 96

(72.18)

60

(24.79)

1

(10.00) 157

(40.78)

Total 133

(100)

242

(100)

10

(100) 385

(100)



H0: There is no significant association between investors‘ type of workplace activity and


H1: There is a significant association between investors‘ type of workplace activity and



Value df Sig.




Cramer‘s V 0.467 0.000



test is presented in Table 4.55. The Pearson Chi-square significance value is 0.000 and


there is a significant association between investors‘ type of workplace activity and their

240

financial literacy level. From the last row of the same table, it is also seen that Cramer‘s

V value is significant with 0.000 and the degree of association between these two

variables is 46.7%.

4.10.8 Association between investors‟ years of work experience and their financial

literacy level

The data regarding investors‘ years of work experience and their financial literacy level is


Table 4.56 Cross Tabulation of Investors‟ Years of Work Experience and Their


Financial

literacy

level

Respondents‟ years of work experience

Total

Less than

five

6 Years to

10 years

11 years to

20 years

21 years to

30 years

More than

30 years

Low 57 44 39 51 37 228

(80.28) (69.84) (50.65) (45.13) (60.66) (59.22)

High 14 19 38 62 24 157

(19.71) (30.16) (49.35) (54.88) (39.34) (40.78)

Total 71 63 77 113 61 385

(100) (100) (100) (100) (100) (100)



H0: There is no significant association between investors‘ years of work experience and


H1: There is a significant association between investors‘ years of work experience and


241


Value df Sig.




Cramer‘s V 0.268 0.000





there is a significant association between investors‘ years of work experience and their

financial literacy level. It might be also concluded that investors‘ years of work

experience and their financial literacy level are not independent of each other. In other

words, these two variables are significantly related. From the last row of the same table, it

is also seen that Cramer‘s V value is significant with 0.000 and the degree of association

between these two variables is 26.8%.

4.10.9 Association between investors‟ years of investment experience and their


The data regarding investors‘ years of investment experience and their financial literacy

level is given in Table 4.58.

242

Table 4.58 Cross Tabulation of Investors‟ Years of Investment Experience and their


Financial

literacy level Years of investment experience

Total

Less than

1year 1-5 years 6-10 years

More than

10 years

Low 69

(98.57)

109

(81.95)

29

(27.88)

21

(26.92)

228

(59.22)

High 1

(1.43)

24

(18.05)

75

(72.12)

57

(73.08)

157

(40.48)

Total 70

(100)

133

(100)

104

(100)

78

(100)

385

(100)



H0: There is no significant association between investors‘ years of investment experience


H1: There is a significant association between investors‘ years of investment experience



Value df

Asymp. Sig.

(2-sided)




Cramer‘s V 0.623 0.000





243

there is a significant association between investors‘ years of investment experience and

their financial literacy level. It might be also concluded that investors‘ years of

investment experience and their financial literacy level are not independent of each other.

In other words, these two variables are significantly associated with each other. From the

last row of the same table, it is also seen that Cramer‘s V value is significant with 0.000

and the degree of association between these two variables is 62.3%.

4.10.10 Association between numbers of times investors shop around and their


The data regarding numbers of times investors shop around and their financial literacy

level is given in Table 4.60.

Table 4.60 Cross Tabulation of Numbers of Times Investors Shop Around and their


Financial

literacy

level

Numbers of times respondents shop around

Total Zero 1 to 3 4 to 6 More than 6

Low 81

(93.10)

122

(80.79)

21

(18.92)

4

(11.11)

228

(59.22)

High 6

(6.70)

29

(19.21)

90

(81.08)

32

(88.89)

157

(40.78)

Total 87

(100)

151

(100)

111

(100)

36

(100)

385

(100)


The hypotheses for the data shown in Table 4.60 for chi-square test are as under.

H0: There is no significant association between numbers of times investors shop around


H1: There is a significant association between numbers of times investors shop around


244


Value Df Sig.





Cramer‘s V 0.683 0.000




there is a significant association between number of times investors shop around and their

financial literacy level. It might be also concluded that number of times investors shop

around and their financial literacy level are not independent of each other. In other words,

these two variables are significantly associated with each other. From the last row of the

same table, it is also seen that Cramer‘s V value is significant with 0.000 and the degree

of association between these two variables is 68.3%.

4.10.11 Association between risk tolerance level of investors and their financial

literacy level

The data regarding risk tolerance level of investors and their financial literacy level is


245

Table 4.62 Cross Tabulation of Risk Tolerance Level of Investors and their


Financial

literacy

level

Respondents‟ risk tolerance level

Total

Lowest Risk

Taker

Moderate

Risk Taker

High Risk

Taker

High Risk

Taker

Low 17

(70.83)

50

(72.46)

73

(52.14)

88

(57.89)

228

(59.22)

High 7

(29.17)

19

(27.54)

67

(47.86)

64

(42.11)

157

(40.78)

Total 24

(100)

69

(100)

140

(100)

152

(100)

385

(100)



H0: There is no significant association between risk tolerance level of investors and their


H1: There is a significant association between risk tolerance level of investors and their



Value Df Sig.




Cramer‘s V 0.156 0.025





there is a significant association between risk tolerance level of investors and their

financial literacy level. It might be also concluded that risk tolerance level of investors

246

and their financial literacy level are not independent of each other. In other words, these

two variables are significantly associated with each other. From the last row of the same

table, it is also seen that Cramer‘s V value is significant with 0.025 and the degree of

association between these two variables is 15.6%.

4.11 Regression analysis

Some of the most interesting questions of statistical analysis revolve around the

relationship among the variables, which is established by regression analysis. Regression

analysis is a tool with several important applications. First, it is a way of testing

hypothesis concerning the relationship between two types of variables. Second, it is a

way of estimating the specific nature of such a relationship. Third, it allows us to predict

the values of one variable, if we know or estimate the other variables.

Logistic Regression

Logistic regression is regularly used rather than discriminant analysis, when there are two

categories of dependent variable. Logistic regression is also easier to use with SPSS than

discriminant analysis when there is a mixture of numerical and categorical independent

variables, because it includes the procedure for generating necessary dummy variables

automatically, requires fewer assumptions, and is more statistically robust (Hair et al.

1999). Discriminant analysis strictly requires the continuous independent variables

(though dummy variables can be used as in multiple regression). Thus, in instances where

the independent variables are categorical, or a mix of continuous and categorical, and

dependent variable is categorical, logistic regression is necessary.

Binomial (or binary) logistic regression is a form of regression which uses binomial

probability theory, does not require linearity of relationship between the independent

variables and the dependent and does not require normally distributed variables.

247

The binary logistic model commonly deals with the issue of how likely an observation is

to belong to each group. It estimates the probability of an observation belonging to a

particular group (Malhotra, 2008373

)

To test the following hypotheses, the logistic regression was used.

H0: There is no significant impact of demographic and socio-economic variables of

investors on their financial literacy level.

H1: There is a significant impact of demographic and socio-economic variables of

investors on their financial literacy level.

To perform logistic regression, for deciding the independent/explanatory variables, the

in-depth review literature that establishes the association between investors‘/consumers‘

demographic and socio-economic variables with their financial literacy level is studied.

The prior research has shown that the level of financial literacy varies with demographic

and socio-economic variables of people. For example, on the variable of gender, female

are less financially literate than male (Chen & Volpe, 2002; Beal & Delpachitra, 2003;

OECD studies, 2005; Lusardi & Mitchell, 2009; Hussein et al., 2009), female are less

knowledgeable in some areas of personal finances (Bakken, 1967; Danes & Hira, 1987;

HSR, 1993; Volpe et al., 1996; Chen & Volpe, 1998) and women experience more

problems in managing their finances than men (Martinez, 1994; Genasci, 1995; Lewin,

1995). With regard to age, prior studies found that not only those who are under the age

of 30 years (Chen & Volpe, 1998; Commonwealth Bank Study, 2004; OECD (U.K.)

Study, 2005), but also, who are at both the extremes of age profile (ANZ Bank Study,

2003; OECD (Australia) Study, 2005) possess lower financial literacy than others.

There is evident that financial literacy does vary with education of an individual. The

studies identified those having lower level of education are less financially literate (Vole

et al., 2002; ANZ Bank Study, 2003; Commonwealth Bank Study, 2004; OECD

373 Malhotra, N. (2008). Marketing Research – An Applied Orientation (5th ed.). New Delhi: Pearson

Education, p. 625.

248

(Australia & Korean) Study, 2005; Hussain et al., 2009). While on the variables of

monthly income, those with lower monthly income are found to be less financially

literate than those withdrawing higher monthly income (Chen & Volpe, 1998; Beal &

Delpachitra, 2003; ANZ Bank Study, 2003; OECD (Australia & U.K.) Studies, 2005).

Studies show that the stage of life cycle is also one of the important predictors of

financial literacy. Past studies found that those who are young single (Chen & Volpe,

1998; Vole et al., 2002; ANZ Bank Study, 2003; Commonwealth Bank Study, 2004;

OECD (Australia & U.K.) Studies, 2005), single parents (Schegen & Lines, 1996) are

less financially knowledgeable than others.

With regard to employment structure, the review of literature concludes employment

structure is one of the important predictor for financial literacy (ANZ Bank Study, 2003;

Commonwealth Bank Study, 2004; OECD (Australia) Study; Hussain et.al., 2009). Prior

literature also suggest that individual‘s financial literacy does vary with years of work

experience they possess (Chen & Volpe, 1998; Beal & Delpachitra, 2003) and type of

workplace activity in which they are engaged in (ANZ Bank Study, 2008; Hussain et. al,

2003).

Several studies have also found the association between financial literacy and years of

investment experience (ANZ Bank Study, 2005) and number of times investors shop

around/make inquiry while investing (ANZ Bank Study, 2005). Prior studies also found

that financial literacy does vary with the risk tolerance of individuals (Beal &

Delpachitra, 2003).

Following the review of literature, in present study, investors‘ demographic and socio-

economic variables such as, investors‘ age, gender, education, monthly income, stage of


experience, number of times shop around while investing and years of investment

experience are considered as determinants of financial literacy for performing logistic

regression. The logistic regression was used to identify the effect of these independent

variables on financial literacy level.

249

The level of financial literacy was used as the dependent variable As explained in

Chapter 3, to measure the financial literacy level of respondents, the respondents‘ total

score was calculated as the percentage of correct answers (Lyons, 2007374

). The survey

responses from each respondent were used to calculate the median percentage of correct

scores for entire survey. The overall scores were grouped into two categories according to

the median percentage of correct scores of all participants of the survey. Accordingly, a

median percentage of correct answers of the sample was considered as a base to frame

financial literacy level of the respondents and/or to classify the subgroups. The

respondents with the scores equal to or below median are considered as respondents with

relatively lower level of financial literacy and hence classified into the first category, i.e.

investors with relatively lower level of financial literacy and respondents with scores

above median are considered as respondents (investors) with higher financial literacy and

hence classified in the second category, i.e. investors with relatively higher level of

financial literacy and hence classified into second category (Volpe et al.,2002375

, Hussein

et al., 2009376

). This dichotomous variable of financial literacy level was used as the

dependent variable.

The independent variables used in the logistic regression are shown in Table 4.64, with

their codes used to get impact on financial literacy. From the Table, it can be seen that the

explanatory variables comprise only categorical. In logistic regression, the metric

variables are treated as ‗covariates‘ and non-metric or categorical variables are treated as

‗factors‘. All the independent variables are fed accordingly in SPSS.

374 Lyons, A., Rachlis, M., & Scherpf, E. (2007). What‘s in a Score? Differences in Consumers‘ Credit

Knowledge Using OLS and Quantile Regressions. Networks financial institute. Indiana University, 2007-WP-01, retrieved on January 21, 2012 from www.networksfinancialinstitute.org 375 Volpe, R. P., Kotel, J. E. & Chen, H. (2002). A survey of investment literacy among online investors,

Financial Counseling and Planning, 13(1), 1-13. 376 Classification/subgroups are made on the basis of Hussein A. H. Al- Tamini & Al Anood Bin Kali

(2009). Financial literacy and investment decision of UAE investors. The Journal of Risk Finance, 10 (5),

Emerald Group Publishing limited, p. 508

250

Table 4.64 Study Variables: Dependent and Independent Variables for Logistic

Regression

Variables

Dependent variables (DV)

Financial Literacy Categorical variables ‗0‘ if respondent possesses lower level

of financial literacy, ‗1‘ if respondent possesses higher level

of financial literacy

Independent (Explanatory) variables (IV)

Gender Dichotomous variable ‗1‘ for male, ‗2‘ for female

Age Multinomial variable with value of ‗1‘ for 18 to 25 years, ‗2‘

for 26 to 35 years, ‗3‘ for 36 to 45 years, ‗4‘ for 46 to 55 years

and ‗5‘ for 56 years and above (ordinal)

Education Multinomial variable with value of ‗1‘ for primary, ‗2‘ for

secondary, ‗3‘ for higher secondary, ‗4‘ for diploma and ‗5‘ for

graduation, ‗6‘ for post graduation (ordinal)

Monthly income Multinomial variable with value of ‗1‘ for upto Rs. 10,000, ‗2‘

for Rs. 10,001 to 15,000, ‗3‘ for Rs. 15,001 to Rs. 20,000, ‗4‘

for Rs. 20,001 to Rs. 25,000 and ‗5‘ for Rs. 25,001 and above

(ordinal)

Stage in family life

cycle

Multinomial variable with value of ‗1‘ for young single, ‗2‘ for

young married without children, ‗3‘for young married with

children, ‗4‘ for middle age married with children and ‗5‘ for

middle age married without dependent children, ‗6‘ for Older

married (ordinal)

Employment

structure

Multinomial variable with value of ‗1‘ full time salaried, ‗2‘

part time salaried, ‗3‘for casual, ‗4‘ for self employed and ‗5‘

for housewife and ‗6‘ retired, unemployed and others

Type of workplace

activity

Dichotomous variable ‗1‘ for working in financial (services)

related industry, ‗2‘ for working in non-financial (services)

related industry

251

(Table 4.64 Continued)

Years of work

experience

Multinomial variable with value of ‗1‘ for less than 5 years, ‗2‘

for 6 to 10 years, ‗3‘ for 11 to 20 years, ‗4‘ for 21 to 30 years

and ‗5‘ for years and more (ordinal)

Number of times

shops around

Multinomial variable with value of ‗1‘ for zero , ‗2‘ for 1 to 3

times, ‗3‘ for 4 to 6 times, ‗4‘ for more than 6 times (ordinal)

Years of investment

experience

Multinomial variable with value of ‗1‘ for less than 1 year, ‗2‘

for 1 to 5 years, ‗3‘ for 6 to 10 years, ‗4‘ for more than 10 years

(ordinal)

Risk tolerance level Multinomial variable with value of ‗1‘ for lowest risk

tolerance, ‗2‘ for moderate risk tolerance, ‗3‘ for high risk

tolerance, ‗4‘ for highest risk tolerance (ordinal)

The logistic regression was used to identify the effect of each of above mentioned

predictors (independent variables/explainable variables) on financial literacy level

(dependent variable). Each independent variable has as many parameters as categories,

but one is redundant, so, researcher needs to specify a reference category. The equation 1,

the coefficients in the regression function represent the effect of each subgroup compared

with a reference group, which is arbitrarily selected. For example, for gender, the

reference category is male, for age, the reference category is age group of 18 to 25 years;

for education, the reference category is Primary, i.e. who has completed primary

education; for monthly income, the reference category is first, i.e. the respondents who

earn monthly income less than Rs. 10,000. Similarly for stage in family life cycle, the

reference category is young single; for employment structure, reference category is

respondent who is full time salaried; for type of workplace activity the reference group is

respondents working in financial services related industry. Reference category for years

of work experience is respondents having a work experience is less than 5 years; for

number of times investor shop around while investing, the reference category is first, i.e.

zero (respondents who do not shop around at all/ do not make inquiry at all while

investing); reference category for years of investment experience is first, i.e. less than 1

252

year. Lastly for risk tolerance, the reference group is respondents with low risk tolerance

level.

In logistic regression, where explanatory variable is categorical, the use of dummy

variables to contrast the different categories are required. For each variable, logistic

regression requires to choose a baseline category and then to contrast all remaining

categories with the base line. If an explanatory variable has k categories, then the

researcher needs k-1 dummy variables to investigate all the differences in the categories

with respect to the dependent variable. For present logistic regression SPSS has created

dummy variables for the researcher from categorical explanatory variables, the in-depth

explanation for dummy variables used in logistic regression is given after the logistic

regression equation formed.

Table 4.65 Case Processing Summary

Unweighted Casesa N Percent

Selected Cases Included in Analysis 385 100.0

Missing Cases 0 0.0

Total 385 100.0

Unselected Cases 0 0.0

Total 385 100.0

a. If weight is in effect, see classification table for the total

number of cases.

While running the logistic regression, the classification Table (Table 4.66 in block 0)

Beginning Block is important to interpret, before deriving final model.

Table 4.65 shows that all 385 cases are considered to perform logistic regression, under

study. As explained in chapter 3, this median percentage of correct scores (i.e. 56) of the

sample was considered to frame financial literacy level and/or to classify the cases in to

different subgroups. The respondents with scores above median were considered as

respondents with higher financial literacy and hence classified as higher financially

literate and respondents with scores equal to and lower than median were considered as

respondents with relatively lower level of financial literacy and hence classified as lower

253

financially literate. To perform the logistic regression, the dependent variable is

considered as financial literacy level of respondents and coded as 0 for ―lower level of

financial literacy‖ and 1 for ―higher level of financial literacy‖. For the present analysis,

the cut off point for classifying the respondents in two categories is 0.56.i.e. median

percentage of correct answers.

Block 0- Beginning Block: Block 0 presents the results with the constant included before

any coefficients (i.e. those relating to independent variables) are entered into the

equation. Logistic regression compares this model with a model including all the

predictors (independent variables) to determine whether the later model is more

appropriate or not. Table 4.66 suggests that if we knew nothing about the predicted

variables under study and guessed that a person would not fall under higher level of

financial literacy, then the result would that only 59.2% cases are correctly classified, as

shown in Table 4.66. Table 4.67 (Variables not in the equation table) shows that whether

each category of independent variables improves the model by its significant value shown

in last column of the Table 4.67, and if these independent/explainable variables/

predictors are included in the table, it would add to the predictive power of the final

model. If they had not been significant and able to contribute to the prediction, then the

termination of the analysis would obviously occur, at this point.

Table 4.66 Classification Tablea,b

Observed

Predicted

Level Percentage

Correct Low High

Step 0 Level Low 228 0 100.0

Higher 157 0 0.0

Overall Percentage 59.2 a. Constant is included in the model. b. The cut value is 0.56

254

Table 4.67 Variables Not in the Equation

Score df Sig.

Step 0 Variables Gender(1) 36.462 1 0.000*

Age 135.818 4 0.000*

Age(1) 27.133 1 0.000*

Age(2) 27.438 1 0.000*

Age(3) 55.365 1 0.000*

Age(4) 0.394 1 0.530

Education 6.545 5 0.257

Education(1) 2.252 1 0.133

Education(2) 0.778 1 0.378

Education(3) 0.105 1 0.746

Education(4) 1.508 1 0.219

Education(5) 0.376 1 0.540

Income 79.469 4 0.000*

Income(1) 8.503 1 0.004*

Income(2) 0.217 1 0.641

Income(3) 29.900 1 0.000*

Income(4) 27.395 1 0.000*

Stageoflife 35.696 5 0.000*

Stageoflife(1) 5.182 1 0.023*

Stageoflife(2) 0.092 1 0.762

Stageoflife(3) 13.897 1 0.000*

Stageoflife(4) 1.723 1 0.189

Stageoflife(5) 3.240 1 0.072**

Employmnt_structure 7.001 5 0.221

Employmnt_structure(1) 1.885 1 0.170




Employmnt_structure(5) 5.000 1 0.025*

Workactivity 83.835 2 0.000*

Workactivity(1) 68.944 1 0.000*

255

Workactivity(2) 4.027 1 0.045*

WorkExperience 27.665 4 0.000*

WorkExperience(1) 3.518 1 0.061**

WorkExperience(2) 2.928 1 0.087**

WorkExperience(3) 13.145 1 0.000*

WorkExperience(4) 0.062 1 0.804

No.oftimesshoparound 179.618 3 0.000*

No.oftimesshoparound(1) 47.881 1 0.000*



InvestmentExperience 149.327 3 0.000*

InvestmentExperience(1) 43.487 1 0.000*



RiiskTolerance 9.366 3 0.025*

RiiskTolerance(1) 6.105 1 0.013*

RiiskTolerance(2) 4.564 1 0.033*

RiiskTolerance(3) 0.183 1 0.669

Overall Statistics 278.295 39 0.000*

*p<.05,

**p<0.1

Table 4.68 shows, at initial step (i.e. step 0), in the constant model without considering

any independent variables in the equation of logistic regression. The significant value is

0.000, which is less than 0.05. Hence, this shows that the researcher can proceed further

for defining final model.

Table 4.68 Variables in the Equation

B S.E. Wald df Sig. Exp(B)

Step 0 Constant -0.373 0.104 12.943 1 0.000* 0.689

*p<0.05

(Table 4.67 Continued)

256

As initial step (step 0), permitted the researcher to go further to explain the effect of

independent variables under study on financial literacy level. Hence, researcher has

proceeded with including the independent variables under study, in the constant logistic

regression model, as explained above.

Once the significance of constant model checked, the researcher has developed the final

model by considering all the independent variables under study, which may determines

the impact of multiple independent variables presented simultaneously to predict

membership of one or other of the two dependent variable categories. Further to assess

whether each of the independent variables included in the model make a significant

contribution to the model, to evaluate the model fit and its significance as well, of the

final model of logistic regression, a variety of statistical tests for model fit are performed,

as shown below.

Model Chi-square

The overall significance is tested by Model Chi square, which is derived from the

likelihood of observing the actual data under the assumption that the model that has been

fitted accurately. Two hypotheses were developed to test in relation to the overall fit of

the model.

H0: The predictors do not have significant effect.

H1: The predictors have a significant effect.

As shown in Table 4.69, present case model chi square has 39 degrees of freedom, a

value of 420.876, with a significant value of 0.000, which is less than 0.05 as shown in

Table 4.69. Hence, we reject the null hypotheses and conclude the predictors do have a

significant effect, with the model containing only the constant indicating that the

predictors do have a significant effect and create essentially a different model. So, we

257

need to look closely at predictors and from the later tables determine whether the

independent variables the significance of predictors.

Table 4.69 Omnibus Tests of Model Coefficients

Chi-square df Sig.

Step 1 Step 420.876 39 0.000

Block 420.876 39 0.000

Model 420.876 39 0.000

Logistic regression employs maximum likelihood procedure through iterations to find out

the most likely estimates for the coefficients. Instead of minimizing the sum of squared

deviations (or least squares differences in ordinary least square method) in multiple

regression, the logistic regression maximizes the likelihood that an event will occur. This

likelihood value is used for assessing the measure of overall model fit. Logistic

regression measures the model estimation fit with the value of -2 time the log of the

likelihood values, referred to as -2LL or -2 log likelihood.

The likelihood ratio test is based on -2LL ratio. It is a test of the significance of the

difference between the likelihood ratio (-2LL) for the researcher‘s model with predictors

(called model chi square) minus the likelihood ratio for baseline model with only a

constant in it. Significance at the 0.05 level or lower means the researcher‘s model with

the predictors is significantly different from the one with the constant only (all ‗b‘

coefficients being zero). It measures the improvement in fit that the explanatory variables

make compared to the null model. Chi square is used to assess significance of this ratio.

The difference between –2LL for the best-fitting model and –2LL for the null hypothesis

model (in which all the b values are set to zero in block 0) is distributed like chi squared,

with degrees of freedom equal to the number of predictors; this difference is the Model

chi square that SPSS refers to. As explained above, the likelihood-ratio test uses the ratio

of the maximized value of the likelihood function for the full model (L1) over the

maximized value of the likelihood function for the simpler model (L0). This log

258

transformation of the likelihood functions yields a chi-squared statistic. Very

conveniently, the difference between -2LL values for models with successive terms

added also has a chi-squared distribution, so when going to a stepwise procedure,

researcher may use chi-square tests to find out if adding one or more extra predictors.

In other words, the overall test of relationship among the independent variables and

groups defined by the dependent is based on the reduction in the likelihood values for a

model which does not contain any independent variables and model that contains the

independent variables. This difference in likelihood follows chi-square distribution as

discussed above, and is referred to as model chi-square. The significance test for the final

model chi-square (after independent variables added) is the researcher‘s statistical

evidence of the presence of a relationship between the dependent variables and the

combinations of the independent variables.

H- L Test

An alternative to model chi-square is the Hosmer and lemeshow test which divides

subject into 10 observed groups of subjects and then compared the number actually in the

each group (observed) to the number predicted by the logistic regression model

(predicted) (Table 4.70).

Table 4.70 Contingency Table for Hosmer and Lemeshow Test

Level = Low Level = High

Total Observed Expected Observed Expected

Step 1 1 39 39.000 0 0.000 39

2 39 38.999 0 0.001 39

3 39 38.989 0 0.011 39

4 38 38.883 1 0.117 39

5 37 37.382 2 1.618 39

6 31 26.529 8 12.471 39

7 4 7.699 35 31.301 39

8 1 0.494 38 38.506 39

259

9 0 0.024 39 38.976 39

10 0 0.001 34 33.999 34

From Table 4.70, it can be seen that the 10 ordered groups are created based on their

estimated probability; those with estimated probability below 0.1form one group, and so

on, up to those with probability 0.9 to 1.0. Each of these categories is further divided into

two groups based on actual observed outcome variable (success, failure). The expected

frequencies for each of the cells are obtained from model. A probability (p) value is

computed from the chi-square distribution with 8 degree of freedom to test the fit of the

logistic model. If H-L goodness of-of-fit test statistic is greater than 0.05, as researcher

wants for well-fitting model, the researcher fails to reject null hypothesis that there is not

difference between observed and model-predicted values, implying that the model‘s

estimates fit the data at an acceptable level. That is, well-fitting models show non-

significance on the H-L goodness-of-fit test. This desirable outcome of non-significance

indicates that model prediction does not significantly differ from the observed.

Table 4.71 Model Fitting Information:

Test of Significance between Independent and Dependent Variable:

Hosmer-Lemeshow Test

Model Chi-square df Sig.

Final 11.930 8 0.154*

*p>0.05

Table 4.71 summarizes the existence of relationship between the independent variables

and the independent variable was supported. Furthermore, the probability of the model

chi-square (11.930 is significant with 0.154), which is higher than the required level of

significance i.e. 5%. This enables the researcher not to reject the null hypothesis and to

conclude that there is no difference between observed and model-predicted values,

implying that the model‘s estimates fit the data at an acceptable level. That is, well fitting

models show non-significance on the H-L goodness-of-fit test concludes that there is no

difference between researcher‘s model (observed) and model predicted by the logistic

regression (predicted) (that SPSS refers to).

260

Thus, the researcher may conclude that the dependent variable is significantly explained

by the given set of independent variables. In other words, independent variables

(predictors) have significant effects in predicting the dependent variable.

Amount of variation explained by the model

After assessing the model fit, it is required to check the strength of relationship between

the independent variables and dependent variable.

Although, there is no close analogous statistic in logistic regression to the coefficient of

determination R2, the logistic regression computes correlation measures to estimate the

strength of the relationship. In logistic regression, commonly used measures of model fit

are based on the likelihood function and are Cox & Snell R square and Nagelkerke’s R

square. Both these measures are similar to R2 in multiple regression and these correlation

measures do not really tell us much about the accuracy or errors associated with the

model. In Table 4.72, the model summary provides approximation only. Cox and Snell‘s

R-square attempts to imitate multiple R-square based ―likelihood‘. The Cox and Snell R

square is constrained in such a way that it cannot equal 1.0, even if the model perfectly

fits the data. This limitation is overcome by the Nagelkerke‘s R square (Malhotra, 2008).

Moreover, Nagelkerke‘s R2

is widely used and the most reported measure of Pseudo R-

square measures among the others such as Cox and Snell. The Nagelkerke modification

that does range from 0 to 1 is a more reliable measure of the relationship. Nagelkerke‘s

R2 is normally be higher than the Cox and Snell measure. For present study, from Table

4.72, indicates that 66.5% of the variation in the dependent variables is explained by the

logistic model. It is also found that Nagelkerke‘s R2 value was (0.897), indicating a

strong relationship of 89.7% between the predictors and the prediction or high level of

percentage variance is explained by the independent variables.

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Table 4.72 Strength of the Relationship Model

Step

-2 Log

likelihood

Cox & Snell

R Square

Nagelkerke R

Square

1 99.678a 0.665 0.897

a. Estimation terminated at iteration number 8 because

parameter estimates changed by less than 0.001.

Variables in the equation:

The variables in the equation Table (Table 4.73), has several important elements. The

Wald statistic and associated probabilities provide an index of significance of each

predictor in the equation. The Wald statistic has a chi-square distribution.

In Table 4.73, in the second column, the value of ‗B‘ is the estimated co-efficient, with

standard error, S.E. (refer third column of the same Table). The ratio of ‗B‘ to S.E.,

squared, equals to Wald statistic. The simplest way to assess Wald statistic is to take the

significant values (as shown in the sixth column of the same table) and if it is less than

0.05, then reject the null hypothesis as the variable does make a significant contribution

and further it is to be concluded that the parameter is useful to the model.

―Exp(B)‖ column in Table 4.73 represents the extent to which raising the corresponding

measure by one unit influences the odd ratio. In other words, ―Exp(B)‖, or odd ratio, is

the predicted change in odds for a unit increase in the predictor. The ―exp‖ refers to the

exponential value of B. When Exp(B) is less than 1, increasing values of the variable

correspond to the decreasing odds of the event‘s occurrence. When Exp(B) is greater than

1, increasing values of the variables correspond to increasing odds of the event‘s

occurrence. In other words, if value of Exp(B) exceeds 1, then odds of an outcome

occurring increase; if the figure is less than 1, any increase in the predictor leads to a drop

in the odds of the outcome occurring.

A Wald test is used to test the statistical significance of each coefficient (b) in the model.

A Wald test calculates a Z statistic. This Z value is then squared, yielding a Wald statistic

with a chi-square distribution.

262

Table 4.73 Significance of each Individual Predictor on Dependent Variable

Categorical Variables B S.E. Wald df Sig. Exp(B)

GENb -- -- -- -- -- --

GEN1 -5.382 1.549 12.074 1 0.001* 0.005

AGEb -- -- -- -- -- --

AGE1 0.512 1.309 0.153 1 0.696 1.668

AGE2 5.648 1.530 13.634 1 0.000* 283.707

AGE3 4.457 1.717 6.734 1 0.009* 86.204

AGE4 1.218 1.790 0.463 1 0.496 3.381

EDUb -- -- -- -- -- --

EDU1 1.544 1.427 1.169 1 0.280 4.681

EDU2 0.790 1.457 0.294 1 0.588 2.203

EDU3 -1.516 1.790 0.717 1 0.397 0.220

EDU4 0.649 1.391 0.217 1 0.641 1.913

EDU5 -2.500 1.715 2.126 1 0.145 0.082

INCb -- -- -- -- -- --

INC1 0.668 1.124 0.353 1 0.553 1.950

INC2 -0.674 1.160 0.338 1 0.561 0.509

INC3 2.428 1.213 4.007 1 0.045* 11.338

INC4 2.349 1.334 3.100 1 0.078**

10.471

LIFESTAGEb -- -- -- -- -- --

LIFESTAGE1 -4.079 1.782 5.241 1 0.022* 0.017

LIFESTAGE2 -2.203 1.593 1.912 1 0.167 0.110

LIFESTAGE3 -3.512 1.797 3.823 1 0.051* 0.030

LIFESTAGE4 -3.014 1.978 2.322 1 0.128 0.049

LIFESTAGE5 -4.453 2.449 3.306 1 0.069**

0.012

EMPTb -- -- -- -- -- --

EMPT1 -1.056 1.323 0.637 1 0.425 0.348

EMPT2 -0.413 2.124 0.038 1 0.846 0.662

EMPT3 -1.555 1.008 2.380 1 0.123 0.211

EMPT4 5.191 2.236 5.388 1 0.020* 179.672

EMPT5 -1.283 1.462 0.770 1 0.380 0.277

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Categorical Variables B S.E. Wald df Sig. Exp(B)

WORKACTIb -- -- -- -- -- --

WORKACTI1 -2.897 0.759 14.575 1 0.000* 0.055

WORKACTI2 -4.937 2.198 5.044 1 0.025* 0.007

WORKEXb -- -- -- -- -- --

WORKEX1 -1.500 1.241 1.460 1 0.227 0.223

WORKEX2 -1.486 1.309 1.288 1 0.256 0.226

WORKEX3 -2.523 1.634 2.385 1 0.123 0.080

WORKEX4 -0.975 1.605 0.369 1 0.543 0.377

NOOFTIMESHOPb -- -- -- -- -- --

NOOFTIMESHOP1 0.521 0.915 0.324 1 0.569 1.683

NOOFTIMESHOP2 6.100 1.369 19.854 1 0.000* 446.063

NOOFTIMESHOP3 5.092 1.756 8.413 1 0.004* 162.760

INVESTEXb -- -- -- -- -- --

INVESTEX1 1.737 1.625 1.143 1 0.285 5.683

INVESTEX2 8.029 2.128 14.233 1 0.000* 3.0693

INVESTEX3 7.423 2.126 12.193 1 0.000* 1.6743

RTb -- -- -- -- -- --

RT1 -1.927 1.377 1.959 1 0.162 0.146

RT2 -0.463 1.573 0.086 1 0.769 0.630

RT3 -1.427 1.819 0.616 1 0.433 0.240

Constant -3.078 3.090 0.992 1 0.319 0.046

Note: b reference category,

*p<0.05, **p<0.1

From Table 4.73, it can be seen that variables GENDER1, AGE2, AGE3, INC3, INC4,

LIFESTAGE1, LIFESTAGE3, LIFESTAGE5, EMPT4, WORKACTI1, WORKACTI2,

NOOFTIMESHOP2, NOOFTIMESHOP3, INVESTEX2 and INVESTEXP3 are found to

be significantly related to financial literacy level.

The co-efficient of GEN1 is negative (B=-5.382) and also negative relationship is

displayed from other measure i.e. value of exponential coefficient (0.005), which is less


264

than 1. This indicates that lower the value of GEN1, predicted probability of gender

belonging to higher level of financial literacy group will decrease by 0.005 times. In other

words, the GEN1(Female) is found to be significant (as p=0.000) with the coefficient

value (-5.382), which indicates that female are more likely to fall under the lower level of

financial literacy group, as its Exp(B) values is 0.005, which is less than 1.

With regard to age, those falling under the age groups of 26 to 35 years (AGE1) are

found to be non-significant, as p=0.696. In fact, those falling under the age group of 36 to

45 (AGE2) and under the age groups of 46 to 55 (AGE3) are found to be significant with

coefficient value of (5.648) (p=0.000) and 4.457 (p=0.009) respectively, and likely to fall

into higher level of financial literacy group. It indicates that increase in age also increases

the probability of having higher level of financial literacy among the age group of 36-45

years and 46 to 55 years. AGE4 (years of 56 and above) (p=0.496) are non significant to


Considering the variable education, all the groups of this variable are found to be non-

significant predictors for financial literacy level.

With regard to monthly income, those investors whose monthly income is Rs. 15,001 to

Rs. 20,000 (INC3) and those whose monthly income is in between Rs. 20,001 to Rs.

25,000 (INC4) are found to be significant predictors with coefficient value of 2.428

(p=0.045) and 2.349 (p=0.078) respectively and are likely to fall into higher level of

financial literacy group. Monthly income more than Rs. 25,001 (INC4) is not a

significant factor for financial literacy level.

With respect to stage of family life cycle, LIFESTAGE1 is significant with coefficient

value of -4.079 (p=0.022) indicating that young married without children are likely to fall

in low financial literacy. Similarly, middle age married with dependent children

(LIFESTAGE3) is found to be significant (p=0.051) with a coefficient value of -3.512

and older married (LIFESTAGE5) with coefficient value of -4.453 is found be significant

(p=0.069) are among the group who are likely to have more tendency to have a low level

of financial literacy. It was also found that LIFESTAGE2 and LIFESTAGE4 i.e. young

265

married with children and middle age married without dependent children are non-

significant predictors for financial literacy level.

Table 4.73 also shows that among the categorical variable belonging to investors‘

employment structure, EMPT1 (those who are part time salaries) (p=0.425), EMPT2

(those who are casual) (p=0.846), EMPT3 (self employed) (p=0.123) and EMPT5

(retired, unemployed, and other) (p=0.380) are found to be non-significant predictors for

financial literacy level, as their respective p values are higher than 0.05 and 0.10. Among

the all the groups of employment structure, only EMPT4, i.e housewife with coefficient

value of 5.191 is found to be positively significant (p=0.020), and which is likely to have

more tendency to fall into higher level of financial literacy, as its Exp(B) value is 179.67,

which is higher than 1.

All the groups of variables of type of workplace activity, both the group variables are

found to be significant predictors for predicting financial literacy level. WORKACTI1

(not working in financial services related industry) and WORKACTI2 (Other) are found

to be significant predictors for financial literacy level, with their coefficient value of -

2.897 (p=0.000) and -4.937 (p=0.025) respectively. Both of those are likely to have more

tendency to belong to lower level of financial literacy as their Exp.(B) values are 0.055

and 0.007 respectively,

Similarly, with regard to number of years of work experience of respondents, all the

group variables are found to be non-significant predictors for financial literacy level.

From the Table 4.73, it can be also seen that the among all the groups of number of times

investors shops around/ make inquiry while investing, the groups NOOFTIMESHOP2

(those who shop around for 4 to 6 times while investing) and NOOFTIMESHOP3 (those

who shop around for more than 6 times while investing) are found to be significant

predictors for financial literacy level, with their coefficient value of 6.100 (p=0.000) and

5.092 (p=0.004) respectively. Both of those are likely to have more tendency to belong to

higher level of financial literacy as their Exp.(B) value is 446.06 and 162.76 respectively,

266

which are far higher than 1. From the same table, it is also found that all these groups are

positively significantly related to the level of financial literacy. Among all, the group

NOOFTIMESHOP1 (those who shop around for 1 to 3 times while investing) is found to

be non-significant predictors for financial literacy level.

With regard to years of investment experience of investors, INVESTEXP2 (those having

the years of investment experience of 6 to 10 years) and INVESTEXP3 (those having the

years of investment experience of more than 10 years) are found to be positively

significant with their coefficient value of 8.029 (p=0.000) and 7.423 (p=0.000), are likely

to fall into relatively higher level of financial literacy as Exp(B) value is 3.07 and 1.67

respectively, which are higher than 1. Among all, the group INVESTEXP1 (those having

the years of investment experience of less than 1 years) is non-significant predictor for

financial literacy level as the p value of this group is 0.285.

Similarly, for risk tolerance, all the group variables are found to be non-significant

predictors for predicting financial literacy level.

Overall, among the all the sub groups, AGE1, AGE4, EDU1, EDU2, EDU3, EDU4,

EDU5, INC1, INC2, INC4, LIFESTAGE2, LIFESTAGE4, EMPT1, EMPT2, EMPT3,

EMPT5, WORKEX1, WORKEX2, WORKEX13, WORKEX4, NOOFTIMESHOP1,

INVESTEX1, RT1, RT2 and RT3are found to be non-significant predictors for financial

literacy level.

Logistic regression gives each predictor (independent variable) a coefficient ‗B‘ which

measures its independent contribution to variations in the dependent variable, the

dependent variable can only takes on one of the two values: 0 or 1.

The logistic regression model is as follows:

267

𝐿𝑜𝑔 𝑝

1 − 𝑝

= B0 + B1(GEN1) + B2(AGE1) + B3(AGE2) + B4(AGE3) + B5(AGE4)

+ B6(EDU1) + B7 (EDU2) + B8(EDU3) + B9(EDU4) +B10(EDU5)

+ B11(INC1) + B12(INC2) + B13(INC3) + B14(INC4) + B15(LIFESTAGE1)

+ B16(LIFESTAGE2) + B17(LIFESTAGE3) + B18(LIFESTAGE4)

+ B19(LIFESTAGE5) + B20(EMPT1) + B21(EMPT2) + B22(EMPT3)

+ B23(EMPT4) + B24(EMPT5) + B25(WORKEX1) + B26(WORKEX2)

+ B27(WORKEX3) + B28(WORKEX27) + B29(NOOFTIMESHOP)

+ B30(NOOFTIMESHOP2) + B31(NOOFTIMESHOP3) + B32(INVESTEX)

+ B33(INVESTEX2) + B34(INVESTEX3) +B35(RT1) + B36(RT2) + B37(RT3)

+ B38(WORKACTI1) + B39(WORKACTI2)

where,

FL = Financial literacy level

P = The probability of a respondent with relatively higher level of

financial literacy

GEN = 1, if respondent is a female, 0 otherwise,

AGE1 = 1, if a respondent is in age group of 26 to 35 years, 0

otherwise,

AGE2 = 1, if a respondent is in age group of 36 to 45 years, 0

otherwise,

AGE3 = 1, if a respondent is in age group of 46 to 55years, 0 otherwise,

AGE4 = 1, if a respondent is in age group of 56 years and above, 0

otherwise,

EDU1 = 1, if a respondent has completed secondary education, 0

otherwise,

EDU2 = 1, if a respondent has completed higher secondary education, 0

otherwise,

EDU3 = 1, if a respondent has completed diploma education, 0

otherwise,

EDU4 = 1, if a respondent has completed graduation , 0 otherwise,

EDU5 = 1, if a respondent has completed post graduation education, 0

268

otherwise,

INC1 = 1, if a respondent‘s monthly income is Rs. 10,000 to Rs.

15,000, 0 otherwise,





INC4 = 1, if a respondent‘s monthly income is Rs. 25,0001 and above,

0 otherwise,

LIFESTAGE1 = 1, if a respondent is young married without children, 0

otherwise,

LIFESTAGE2 = 1, if a respondent is young married with children, 0 otherwise,

LIFESTAGE3 = 1, if a respondent is middle age married with dependent

children, 0 otherwise,

LIFESTAGE4 = 1, if a respondent is middle age married without dependent

children, 0 otherwise,

LIFESTAGE5 = 1, if a respondent is older married, 0 otherwise,

EMPT1 = 1, if a respondent is part time salaried, 0 otherwise,

EMPT2 = 1, if a respondent is casual, 0 otherwise,

EMPT3 = 1, if a respondent is self employed, 0 otherwise,

EMPT4 = 1, if a respondent is housewife, 0 otherwise,

EMPT5 = 1, if a respondent is retired, unemployed and others, 0

otherwise,

WORKEXP1 = 1, if a respondent‘s work experience is 6 to 10 years, 0

otherwise,


otherwise,


otherwise,

WORKEXP4 = 1, if a respondent‘s work experience is more than 30 years, 0

otherwise,

269

NOOFTIMESHOP1 = 1, if respondent shop around 1 to 3 times, 0 otherwise

NOOFTIMESHOP2 = 1, if respondent shop around 4 to 6 times, 0 otherwise

NOOFTIMESHOP3 = 1, if respondent shop around more than 6 times, 0 otherwise

INVESTEXP1 = 1, if a respondent‘s investment experience is 1 to 5 years, 0

otherwise,

INVESTEXP2 = 1, if a respondent‘s work experience is 6 to 10 years, 0

otherwise,

INVESTEXP3 = 1, if a respondent‘s work experience is more than 10 years, 0

otherwise,

RT1 = 1, if a respondent is moderate risk tolerance is , 0 otherwise,

RT2 = 1, if a respondent is higher risk tolerance, 0 otherwise,

RT3 = 1, if a respondent is highest risk tolerance, 0 otherwise,

WORKACTI1 = 1, if a respondent not working in finance related workplace

activity, 0 otherwise,

WORKACTI2 = 1, if a respondent‘s work activity is other, 0 otherwise,

Model fit

How good the classification model (after including all the independent variables under

study) is? The answer to this question is given in classification table as shown in the

Table 4.74. The classification table helps the researcher to assess the performance of the

model by cross-tabulating the observed response categories with the predicted response

categories. From Table 4.74, it is found that 95.6 % respondents were correctly classified.

The table also shows that out of 235 cases predicted to be under low financially literate

group, 223 cases were observed to be in low financially literate group, while 12 were in

high financially literate group. Similarly, out of 150 cases predicted to be high financially

literate group, 145 were correctly classified as high financially literate, while only 5 cases

are under low financially literate group. So, out of total 385 cases, 368 (223+145) were

correctly classified and only 17(12+5) cases were misclassified. From this, it can be said

that (385-17)/385, or 95.60% of the cases were correctly classified with this model.

270

Table 4.74 Classification Tablea

Observed

Predicted

Level Percentage

Correct Low High

Step 1 Level Low 223 05 97.80

High 12 145 92.40

Overall Percentage 95.60

a. The cut off value is 0.56

By adding all the independent variables under study in the constant logistic regression, as

explained above, it was found that after adding all the independent variables under study,

now overall 95.60 % of respondents are correctly classified, as shown in Table 4.74. In

other words, researcher can predict the final model with 95.60 % of accuracy, which was

earlier 59.20% only (see Table 4.66).

Thus, to sum up, a logistic regression analysis was conducted to predict the investors‘

financial literacy i.e. higher level of financial literacy or low level of financial literacy by

using the responses from 385 respondents‘ age, gender, education, monthly income, stage

of family life cycle, employment structure, type of workplace activity, years of work

experience, number of times respondents shop around, years of investment experience

and risk tolerance level as predictors (explainable variables/ independent variables). A

test of final model against constant model was statistically significant, indicating that the

predictors as a set reliably distinguished between higher and lower level of financial

literacy (chi square = 420.876, p < 0.05, with df =39).

Nagelkerke‘s R2

with value of 0.897 indicated that a strong relationship between

prediction and grouping. The overall prediction success was 95.60% (97.8% for lower

level of financial literacy and 92.4% for higher level of financial literacy). The Wald

criterion demonstrated that except education, monthly income, and risk tolerance level,

all the predictors are important to predict financial literacy level.

271

Classification Plot

The Fig. 4.7 is a classification plot or histogram of predicted probabilities provides a

visual demonstration of the correct and incorrect predictions. Also called the ‗classplot‘

or the ‗plot of observed groups and predicted probabilities‘. From the graph, it can be

seen that X axis is the predicted probability from 0.0 to 1.0 of the dependent being

classified ‗1‘. The Y axis is frequency: the number of cases classified. A researcher must

look for the following points while analyzing the classification plot.

1) This classification plot should be U –shaped. In logistic regression, U-shaped rather

than Normal distribution is desirable. A U-shaped distribution indicates the

predictions are well-differentiated with cases clustered at each end showing correct

classification.

2) There should be few errors. The ‗H‘s‘ to the left are false positive. The ‗L‘s‘ to the

right are false negatives.

272

Step number: 1

Observed Groups and Predicted Probabilities

160 ┼H ┼

│L │

│L │

F │L │

R 120 ┼L ┼

E │L │

Q │L H│

U │L H│

E 80 ┼L H┼

N │L H│

C │L H│

Y │L H│

40 ┼L H┼

│L H│

│LH H│

│LLLL HH│

Predicted ─────────┼─────────┼─────────┼─────────┼─────────┼─────────┼─────────┼─────────┼─────────┼──────────

Prob: 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1

Group: LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

Predicted Probability is of Membership for High

The Cut Value is .56

Symbols: L - Low

H - High

Each Symbol Represents 10 Cases.

Fig. 4.7 Classification Plot

273


expenditure to monthly income ratio.

The data regarding investors‘ financial literacy level and their monthly expenditure to

monthly income ratio is given in Table 4.75.

Table 4.75 Cross Tabulation of Investors‟ Financial Literacy Level and their

Monthly Expenditure to Monthly Income Ratio

Monthly expenditure

to monthly income

ratio

Respondents with

lower level of

Financial Literacy

Respondents with

higher level of

Financial Literacy Total

1% to 50% 88 38 126

51% to 60% 57 32 89

61% to 70% 40 43 83

71% to 80% 22 30 52

81% to 90% 18 12 30

More than 90 % 3 2 5

Total 228 157 385


performed. Although there are no assumptions made as to the shape of data distribution






). Based on



5, as indicated in the Table 4.75. Hence regrouping is done by combining the cells, which

has expected count less than 5. The new table free from this limitation is as shown below.

377 Luck, D. & Rubin, D. (2003). Marketing Research (7th ed.). New Delhi: Prentice Hall of India Pvt. Ltd.,

p. 347

274

Table 4.76 Revised Cross Tabulation of Investors‟ Financial Literacy Level and

their Monthly Expenditure to Monthly Income Ratio

Monthly expenditure to

monthly income ratio

Investors with

lower level of

Financial

Literacy

Investors with

higher level of

Financial

Literacy Total

1% to 50% 88 38 126

51% to 60% 57 32 89

61% to 70% 40 43 83

71% to 80% 22 30 52

81% to 90% and more than 90% 21 14 35

Total 228 157 385

Hypotheses for the data presented in Table 4.76 for chi-square test are as under

H0: There is no significant association between financial literacy level of investors and

their monthly expenditure to monthly income ratio.

H1: There is a significant association between financial literacy level of investors and

their monthly expenditure to monthly income ratio.


Value df Sig.

Pearson Chi-Square 17.091a 4 0.002



Phi 0.211 0.002

Cramer's V 0.211 0.002





of freedom is 4. Therefore, null hypothesis is rejected and hence, it found that there is a

significant association between financial literacy level of investors and their monthly

275

expenditure to monthly income ratio. It might be concluded that there is an association of

financial literacy level of investors with their monthly expenditure to monthly income

ratio or financial literacy level of investors and their monthly expenditure to monthly

income ratio are not independent of each other. In other words, these two variables are

significantly associated with each other.

Chi square test shows the statistical significance between the two variables. It does not

tell us the strength of association between two variables in the cross tabulation. To

measure the strength of this association, The Cramer‘s V, one of the measures of indexes

of agreement is used, which is shown in the Table 4.77. From the table, it can be seen that

the value of Cramer‘s V significant with 0.002 and the degree of association is between

the variables is 21.1%.


saving to monthly income ratio.

The data regarding the investors‘ financial literacy level and their monthly saving to

monthly income ratio is given in Table 4.78.

Table 4.78 Cross Tabulation of Investors‟ Financial Literacy and their Monthly

Saving to Monthly Income Ratio

Monthly saving to

monthly income

ratio

Investors with

lower level of

Financial Literacy

Investors with

higher level of


1% to 50% 183 34 217

51% to 60% 43 84 127

61% to 70% 2 38 40

71% to 80% 0 1 1

Total 228 157 385


performed. Although there are no assumptions made as to the shape of data distribution


276





). Based on



5, as indicted in the Table 4.78. Hence regrouping is not done by combining. The new

Table free from this limitation is as shown below.

Table 4.79 Revised Cross Tabulation of Investors‟ Financial Literacy Level and

their Monthly Saving to Monthly Income Ratio

Monthly saving to

monthly income ratio

Respondents with

lower level of

Financial Literacy

Respondents with

higher level of


1% to 50% 183 34 217

51% to 60% 43 84 127

61% to 80% and more

than that 02 39 41

Total 228 157 385

Hypotheses for the data presented in Table 4.79 for chi-square test are as under:

H0: There is no significant association between financial literacy level of investors and


H1: There is a significant association between financial literacy level of investors and


378 Luck, D. & Rubin, D. (2003). Marketing Research (7th ed.). New Delhi: Prentice Hall of India Pvt. Ltd.,

p. 347

277


Value df Sig.



Linear-by-Linear

Association 137.105 1 0.000

Phi 0.604 0.000

Cramer's V 0.604 0.000





of freedom is 2. Therefore, null hypothesis is rejected and hence, it found that there is a

significant association between financial literacy level of investors and their monthly

saving to monthly income ratio. It might be concluded that there is an association of

financial literacy level of investors with their monthly saving to monthly income ratio or

financial literacy level of investors and their monthly saving to monthly income ratio are

not independent of each other. In other words, these two variables are significantly

associated with each other.

As, we have discussed earlier, Chi-square test shows the statistical significance between

the two variables. It does not tell us the strength of association between two variables in

the cross tabulation. To measure the strength of this association, The Cramer‘s V, one of

the measures of indexes of agreement is used, which is shown in the Table 4.80. From the

Table 4.80, it can be seen that the value of Cramer‘s V significant with 0.000 and the

degree of association is between the variables is 60.4%.

278

4.14 Regression Analysis: Impact of financial literacy on investment decision

To test the last hypothesis, the simple linear regression model was used.

Regression is a simple statistical tool used to model the dependence of a variable on one

(or more) explanatory variables. This functional relationship may then be formally stated

as an equation, with associated statistical values that describe how well this equation fits

the data. Usually, the investigator seeks to ascertain the causal effect of one variable upon

another. To explore such issues, the investigator assembles data on the underlying

variables of interest and employs regression to estimate the quantitative effect of the

causal variables upon the variable that they influence. The investigator also typically

assesses the ―statistical significance‖ of the estimated relationships, that is, the degree of

confidence that the true relationship is close to the estimated relationship.

Linear regression analysis is a bi-variate statistical technique used to examine the

relationship between a single dependent variable and single independent variable. The

objective of linear regression is to use independent variable whose value is known to

predict the single dependent value selected by the researcher. The independent variable

weighted by the regression analysis procedure to ensure its maximal prediction on the

value of dependent variable. The weight denotes the relative contribution of independent

variable to the overall prediction and facilitate interpretation as to the influence of

independent variable in making the prediction.

Thus, regression analysis with a single explanatory variable is termed ―simple

regression.‖ Then, the hypothesized relationship between financial literacy and

investment decision may be written as:

I = + E +

Where,

279

The variable I is termed the ―dependent‖ variable (I = investment decision); E is termed

the ―independent,‖ or ―explanatory,‖ variable (E = financial literacy level); is the

―constant term‖ and the ―coefficient‖ of the variable E (financial literacy level).

One of the most widely used statistical techniques is simple linear regression. This

technique is used to relate a measured response variable, Y, to a single measured

predictor (explanatory) variable, X, by means of a straight line. It uses the principle of

least squares to come up with values of the ―best‖ slope and intercept for a straight line

that approximates the relationship. The purpose of simple linear regression is to come up

with a straight line that captures the relationship between the predictor and the response

variable.

Measurement used in simple linear regression analysis

Regression co-efficient: Regression co-efficient is the standardized regression co-

efficient that allows for a direct for direct comparison between coefficients as to their

relative explanatory power of dependent variable (Malhotra and Dash, 2010379

).

Coefficient of determination: It is a measure of the proportion of the variance of the

dependent variable about its mean that is explained by the independent or predictable

variable/s. The strength of association is measure by the coefficient of determination.

Its value varies from 0 to 1. The researcher can infer that the higher the value of R2,

greater the explanatory power of the regression equation and therefore the better the

prediction of the dependent variable (Malhotra and Dash, 2010).

Adjusted R2: It is the modified measure of the coefficient of determination that takes

into account the number of independent variables included in the regression equation

and the sample size. It explains whether or not the inclusion of additional independent

379 Malhotra, N. & Dash, S. (2010). Marketing Research: An Applied Orientation (6th ed.).New Delhi:

Pearson Education.

280

variables in regression equation may increase or reduce the overall coefficient of

determination (Malhotra and Dash, 2010)

ANOVA (F-test): The F-test is used to test the significance of the overall regression

equation. It is used to test that the coefficient of multiple determination in the

population is non zero (Malhotra and Dash, 2010).

To test the impact of financial literacy level on investment decision, the following

hypotheses are framed.

H0: There is no significant impact of financial literacy level on investment decision of

investors.

H1: There is a significant impact of financial literacy level on investment decision of

investors.

As explained above, to test this hypothesis, the simple liner regression model is

performed as under. To perform the regression analysis, financial literacy level is

considered as an independent variable and nine factors extracted by factor analysis

independently and simultaneously are taken as factors investment decision and are

considered as dependent variables for regression analysis.

Further, to show the overall impact of financial literacy level (FLL) on investment

decision, the sum of all nine investment factors are considered as dependent variable to

run the regression analysis.

4.14.1 Regression analysis: Financial literacy level and Factor 1-Personal Financial

Need

To check the impact of financial literacy level on investment decision, the financial

literacy level is considered as independent variable and Factor 1: Personal financial need

281

(as a factor for investment decision) is considered as dependent variable. The results of

correlation and regression are shown in following tables with interpretation.

Table 4.81 Correlations between FLL and Personal Financial Need

** Correlation is significant at the 0.05 level (2-tailed).

Table 4.81 shows that the correlation coefficient of two variables under study is 0.882.

This value of r suggests a strong positive linear correlation since the value is positive and

close to 1. Since, there is a strong positive linear relationship between financial literacy

level and Factor 1: personal financial need. Hence, the researcher may go for linear

simple regression analysis. The results of regression analysis performed for these two

variables are presented below.

Table 4.82 Model Summary

Model R R Square Adjusted R2 Std. Error of the Estimate

1 0.882a 0.778 0.777 0.46174

a. Predictors: (Constant), FLL

Table 4.83 ANOVAb

Model Sum of Squares df

Mean

Square F Sig.

1 Regression 285.11 1 285.511 1.339 0.000a

Residual 81.656 383 0.213

Total 367.167 384


b. Dependent Variable: FACTOR1

FLL Factor 1

FLL Pearson Correlation 1 0.882**

Sig. (2-tailed) 0.000

N 385 385

Factor 1 Pearson Correlation 0.882**

1


N 385 385

282

Table 4.84 Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

T Sig. B Std. Error Beta

1 (Constant) 0.512 0.071 7.174 0.000

Level 1.752 0.048 0.882 36.595 0.000

a. Dependent Variable: FACTOR1

The regression analysis was done to measure the variation in personal financial need

(dependent variable), based on variation in financial literacy level (FLL) (independent

variable). From Table 4.84, the following regression equation is derived.

Personal Financial Need = 0.512 + 1.752 (FLL)

In the present regression analysis, the measure of strength of association is given by the

coefficient of determination denoted by R2. From Table 4.82, it can be seen that the R

2

value is 0.778, which shows 77.8 % of variance in investor‘s personal financial need (as a

factor of investment decision) can be predicted by his/her financial literacy level. In other

words, 22 % (1.000-0.778=0.222) in investor‘s personal financial need cannot be

predicted by his/her financial literacy level. The regression equation appears to be very

useful for making predictions, since the value of R2 is close to 1. The last column of the

same table ―standard error of estimation‖ provides a measure of how accurately the

regression equation predicts values of dependent variable. The smaller the value of

standard error of estimation is, better one can predict that the independent variable (i.e.

Financial literacy level) account for the variance in the dependent variable.

The t-test value for the significance of individual independent variable indicates the

significance at 95% confidence level. Table 4.84 shows that financial literacy level (FLL)

is statistically significant with a value of 0.000, which is less than 0.05. The result of F-

test shown in Table 4.83 is also significant with value of 0.000, which allows a researcher

to determine whether or not the linear regression was statistically significant. This

indicates that model is statistically significant at a confidence level of 95%.

283

4.14.2 Regression analysis: Financial literacy level and Factor 2- Accounting,

Business and Financial Information


literacy level is considered as independent variable and Factor 2: Accounting, Business

and Financial Information (as a factor for investment decision) is considered as a

dependent variable. The results of correlation and regression are shown in following

tables with interpretation.

Table 4.85 Correlations between FLL and Accounting, Business and Financial

Information

FLL Factor 2

FLL Pearson Correlation 1 0.042


N 385 385

Factor 2 Pearson Correlation 0.042 1


N 385 385

Table 4.85 shows that the correlation coefficient of two variables under study is 0.042

with a significant value of 0.416, which is higher than 0.05 at 5 % level of significance.

This value of r suggests that there is no correlation between the variables under study.

Therefore, it is concluded that there is no relationship between financial literacy level and

Factor 2: Accounting, business and financial information, and hence, the researcher

should not go for regression analysis.

4.14.3 Regression analysis: Financial literacy level and Factor 3- Economic and

Regulatory Environment


literacy level is considered as an independent variable and Factor 3: Economic and

284

regulatory environment (as a factor for investment decision) is considered as a dependent

variable. The results of correlation and regression analysis are shown in following tables

with interpretation.

Table 4.86 Correlations between FLL and Economic and Regulatory Environment

FLL Factor 3

FLL Pearson Correlation 1 -0.022


N 385 385

Factor 3 Pearson Correlation -0.022 1


N 385 385

Table 4.86 shows that the correlation coefficient of two variables under study is -0.022

with significant value of 0.673. This value is higher than 0.05 at 5% level of significance.



Factor 3: Economic and regulatory environment. Hence, the researcher should not go for

regression analysis.

4.14.4 Regression analysis: Financial literacy level and Factor 4 – Operational

Feedback


literacy level is considered as an independent variable and Factor 4: Operational

Feedback (as a factor for investment decision) is considered as a dependent variable. The

results of correlation and regression analysis are shown in following tables with

interpretation.

285

Table 4.87 Correlations between FLL and Operational Feedback

FLL Factor 4



N 385 385



N 385 385


with a significant value of 0.416, which is higher than 0.05 at 5% level of significance.



Factor 4: Operational feedback. Hence, the researcher should not go for regression

analysis.

4.14.5 Regression analysis: Financial literacy level and Factor 5- Advocate

recommendation


literacy level is considered as an independent variable and Factor 5: Advocate

recommendation (as a factor for investment decision) is considered as a dependent

variable. The results of correlation and regression analysis are shown in the following

tables with interpretation.

Table 4.88 Correlations between FLL and Advocate recommendation

FLL Factor 5



N 385 385


1


N 385 385

**Correlation is significant at the 0.05 level (2-tailed).

286


with significant value of 0.000. This positive value of r suggests a positive linear

correlation between the variables under study. Since, there is a positive linear relationship

between financial literacy level and Factor 5: Advocate recommendation. Hence, the

researcher may go for linear simple regression analysis. The results of regression analysis

performed for these two variables are presented below.


Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 0.261a 0.068 0.066 0.4555


Table 4.90 ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 5.833 1 5.833 28.112 0.000a

Residual 79.477 384 0.208

Total 85.310 385


Dependent Variable: FACTOR5


Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 3.384 0.070 48.044 0.000

Level 0.250 0.047 0.261 5.032 0.000


The regression analysis was done to measure the variation in advocate recommendation



287

Advocate recommendation = 3.384 + 0.250 (FLL)



2

value is 0.068, which shows 6.8 % of variance of investor‘s advocate recommendation

(as a factor of investment decision) can be predicted by his/her financial literacy level. In

other words, 93 % (1.000 -0.068=0.932) in investor‘s advocate recommendation cannot

be predicted by his/her financial literacy level. The last column of the Table 4.89 shows

―standard error of estimation‖, that provides a measure of how accurately the regression

equation predicts values of dependent variable. The smaller the value of standard error of

estimation is, better one can predict that the independent variable (i.e. Financial literacy

level) account for the variance in the dependent variable.







4.14.6 Regression analysis: Financial literacy level and Factor 6-Overall Group

Performance


literacy level is considered as an independent variable and Factor 6: Overall group

performance (as a factor for investment decision) is considered as a dependent variable.

The results of correlation and regression analysis are shown in following tables with

interpretation.

288

Table 4.92 Correlations between FLL and Overall Group Performance

FLL Factor 6



N 385 385


1


N 385 385

** Correlation is significant at the 0.05 level (2-tailed).

Table 4.92 shows that the correlation coefficient of two variables under study is 0.352,

with significant value of 0.000, which is lower than 0.05, at 5 % level of significance.

This value of r suggests a linear correlation between financial literacy level and overall

Factor 6: Overall group performance. Since, there is a positive linear relationship

between variables; the researcher may go for linear simple regression analysis. The

results of regression analysis performed for these two variables are presented below.


Model R R Square

Adjusted R

Square Std. Error of the Estimate

1 0.352a 0.124 0.122 0.65412


Table 4.94 ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 23.226 1 23.226 54.283 0.000a

Residual 163.875 384 0.428

Total 187.101 385

b. Dependent Variable: FACTOR6

289


Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) 2.540 0.101 25.107 0.000

Level 0.500 0.068 0.352 7.368 0.000


The regression analysis was done to measure the variation in overall group performance



Overall Group Performance = 2.540 + 0.500 (FLL)



2

value is 0.124, which shows 12.4 % of variance in investor‘s overall group performance

(as a factor of investment decision) can be predicted by his/her financial literacy level. In

other words, 87.6 % (1.0 – 0.124=0.876) variation in overall groups performance cannot

be predicted by his/her financial literacy level. The regression equation appears to be very

useful for making predictions, since the value of R2 is close to 1. The last column of the

same table ―standard error of estimation‖ provides a measure of how accurately the

regression equation predicts values of dependent variable. The smaller the value of

standard error of estimation is, better one can predict that the independent variable (i.e.

Financial literacy level) account for the variance in the dependent variable.







290

4.14.7 Regression analysis: Financial literacy level and Factor 7-Credit Features


literacy level is considered as an independent variable and Factor 7: Credit feature (as a

factor for investment decision) is considered as a dependent variable. The results of

correlation and regression analysis are shown in following tables with interpretation.

Table 4.96 Correlations between FLL and Credit Features

FLL Factor7



N 385 385

Factor7 Pearson Correlation 0.045 1


N 385 385





Factor 7: Credit features. Hence, the researcher should not go for regression analysis.

4.14.8 Regression analysis: Financial literacy level and Factor 8- Personal

Inclination


literacy level is considered as an independent variable and Factor 8: Personal inclination

(as a factor for investment decision) is considered as a dependent variable. The results of

correlation and regression analysis are shown in following tables with interpretation.

291

Table 4.97 Correlation between FLL and Personal Inclination

FLL Factor 8

FLL Pearson Correlation 1 -0.057


N 385 385

Factor 8 Pearson Correlation -0.057 1


N 385 385

Table 4.97 shows that the correlation coefficient of two variables under study is -0.057,




Factor 8: Personal inclination. Hence, the researcher should not go for regression

analysis.

4.14.9 Regression analysis: Financial literacy level and Factor 9-Monetary

expectation


literacy level is considered as an independent variable and Factor 9: Monetary

expectation (as a factor for investment decision) is considered as a dependent variable.

The results of correlation and regression analysis are shown in following tables with

interpretation.

Table 4.98 Correlations between FLL and Monetary Expectation

FLL Factor 9



N 385 385



N 385 385

p < 0.10

292


with a significant value of 0.076. This significant value is lower than 0.10 at 10% level of

significance. This value of r suggests that there is a correlation between the variables

under study. Since, there is a positive linear relationship between variables; the researcher

may go for linear simple regression analysis. The results of regression analysis performed

for these two variables are presented below.

4.99 Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .090a .008 .006 .491

a. Predictors: (Constant), FACTOR9

4.100 ANOVAb

Model

Sum of

Squares df Mean Square F Sig.

1 Regression .760 1 .760 3.157 .076a

Residual 92.216 383 .241

Total 92.977 384

a. Predictors: (Constant), FACTOR9

b. Dependent Variable: Level

4.101 Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) 1.121 .163 6.868 .000

FACTOR9 .071 .040 .090 1.777 .076

a. Dependent Variable: Level

The regression analysis was done to measure the variation in monetary expectation



293

Monetary Expectation = 1.121 + 0.071 (FLL)



2

value is 0.008, which shows 0.8 % of variance in investor‘s monetary expectation (as a

factor of investment decision) can be predicted by his/her financial literacy level. In other

words, 99.2 % (1.0 – 0.008=0.992) variation in monetary expectation cannot be predicted

by his/her financial literacy level. The last column of the same table ―standard error of

estimation‖ provides a measure of how accurately the regression equation predicts values

of dependent variable. The smaller the value of standard error of estimation is, better one

can predict that the independent variable (i.e. Financial literacy level) account for the

variance in the dependent variable. For these variables standard error of estimation is

49.1%.


significance at 90% confidence level. Table 4.101 shows that financial literacy level

(FLL) is statistically significant with a value of 0.076, which is less than 0.10. The result

of F-test shown in Table 4.100 is also significant with value of 0.076, which allows a

researcher to determine whether or not the linear regression was statistically significant.

This indicates that model is statistically significant at a confidence level of 90%.

4.14.10 Regression analysis: Financial literacy level and sum of investment decision

factors


literacy level is considered as an independent variable and sum of investment decision

factors is considered as a dependent variable. The results of correlation and regression

analysis are shown in following tables with interpretation.

294

Table 4.102 Correlations between FLL and sum of Investment Decision Factors

FLL

Sum of

Investment

Decision Factors



N 385 385

Sum of

Investment

Decision

Factors

Pearson Correlation 0.513**

1


N 385 385

*Correlation is significant at the 0.05 level (2-tailed).


with a significant value of 0.000, which is lower than 0.05 at 5% level of significance.

This value of r suggests a strong positive linear correlation between financial literacy

level and sum of investment factors. Hence, the researcher may go for linear simple

regression analysis.


Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 0.513a 0.263 0.261 0.24539


Table 4.104 ANOVAb

Model

Sum of

Squares Df

Mean

Square F Sig.

1 Regression 8.237 1 8.237 136.794 0.000a

Residual 23.062 384 0.060

Total 31.299 385


b. Dependent Variable: OVERALLFACTOR

295


Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) 3.118 0.038 82.171 0.000

Level 0.298 0.025 0.513 11.696 0.000

a. Dependent Variable: OVERALLFACTORS

The regression analysis was done to measure the variation in investment decision



Investment Decision = 3.118 + 0.298 (FLL)


coefficient of determination denoted by R2. From the Table 4.103, it can be seen that the

R2 value is 0.263, which shows 26.30% of variance in investors‘ investment decision can

be predicted by his/her financial literacy level. In other words, 73.7 % (1-0.263=0.737) in

investors‘ investment decision cannot be predicted by his/her financial literacy level. The

regression equation appears to be very useful for making prediction, since value of R2

is

closer to 1. The last column of the same table ―standard error of estimation‖ provides a

measure of how accurately the regression equation predicts values of dependent variable.

The smaller the value of standard error of estimation is, better one can predict that the

independent variable (i.e. Financial literacy level) account for the variance in the

dependent variable. For these two variables the value of standard error of coefficient is

24.54 %.


significance at 95% confidence level. Table 4.105 shows that financial literacy level

(FLL) is statistically significant with a value of 0.000, which is less than 0.05. The result

of F-test shown in Table 4.104 is also significant with value of 0.000, which allows a

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researcher to determine linear regression is statistically significant. This indicates that

model is statistically significant at the confidence level of 95 %.

Hence, the null hypothesis ―There is no significant impact of financial literacy level on

investment decision of investors‖ is rejected, as significant value 0.000 is less than 0.05

at 5% level of significance. Hence, it may conclude that there is a significant impact of

financial literacy level on investment decision.

Table 4.106 summarizes the result of overall regression analysis done to study the impact

of financial literacy level on investment decision of investors.

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Table 4.106 Summary of Regression Analysis of Financial Literacy Level and Investment Decision

Factors R2 Adj.

R2

S.E. of

estimates

Beta t -

value

Sig. F-test Sig.

Personal financial need 0.778 0.777 2.462 0.882 36.59 0.000* 1.339 0.000

*

Accounting, business and financial

information

0.002 0.000 0.526 0.042 0.814 0.416 0.663 0.416

Economic and regulatory environment 0.000 -0.002 0.622 -0.022 -0.423 0.673 0.179 0.673

Advocate recommendation 0.002 0.000 0.827 0.042 0.815 0.416 0.664 0.416

Operational feedback 0.068 0.066 0.456 0.261 5.032 0.000* 28.112 0.000

*

Overall group performance 0.124 0.122 0.654 0.352 7.368 0.000* 54.283 0.000

*

Credit features 0.002 0.000 0.566 0.045 0.876 0.382 0.767 0.382

Personal inclination 0.003 0.001 0.670 -0.057 -1.114 0.266 1.240 0.266

Monetary expectations 0.008 0.006 0.624 0.090 1.777 0.076**

3.157 0.076**

Sum of investment factors 0.263 0.261 0.245 0.513 11.696 0.000* 136.794 0.000

*

*p<0.05, significant at 0.05,

**p<0.1, significant at 0.1

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4.15 Conclusion

In-depth analysis of data that was collected by administrating the research instrument to

retail individual investors in the state of Gujarat, is presented in this chapter by

employing various univariate, bivarate and multivariate techniques of data analysis. The

results of the statistical tests presented in this chapter are also supported with in-depth

interpretation and explanation of results of each statistical test. The next chapter deals

with the findings of this research study based on the data analysis presented in this

chapter.

Findings

and Conclusion

Chapter 5

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5.1 Introduction

5.2 Summary of the study

5.3 Findings of the study

5.3.1 Findings for the analysis of financial literacy questions

5.3.2 Findings for analysis of existing investment pattern, investment

objectives and preferences for various investment alternatives

5.3.3 Findings for analysis of variables preferred as Sources of

Information while investment

5.3.4 Findings for Factor Analysis performed for variables influencing

Investment Decision of Investors

5.3.5 Findings for the Cross –tabulation and Chi-square test performed

to know association between each demographic and socio-economic

variable of investors and their financial literacy level

5.3.6 Findings for Logistic Regression performed to assess the combine

impact of Demographic and Socio-economic variables of Investors

on their Financial Literacy Level

5.3.7 Findings for the Cross –tabulation and Chi-square test performed

to know association between each financial literacy level of investors

and their monthly expenditure to monthly income ratio and

monthly saving to monthly income ratio

5.3.8 Findings of correlation and regression performed to assess the

impact of financial literacy level of investors on their investment

decision

5.4 Conclusion

5.5 Recommendations

5.5.1 For Policy makers and regulatory authorities

5.5.2 For Investors

5.5.3 For Financial Education Providers

5.6 Limitations of the study

5.7 Scope for further research

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5.1 Introduction

The purpose of this chapter is to present the conclusions in light of the research

objectives presented in chapter 3. The chapter begins with the summary of the study

followed by conclusion and limitations of the study. Future scope for the research is also

discussed. Detailed discussions on major findings are the thrust of this chapter. The

significance of the research is also simultaneously presented.

5.2 Summary of the study

The chapter 1 has begun with the background of the research topic. Researcher has

explained the rationale for selecting the topics for the study. The detailed explanation

was given for need to be a financially literate in today‘s context. Before presenting the

historical developments those taken place while explaining the composite definition of

financial literacy, it is necessary to understand the meaning of ‗literacy‘ first and the

scope of this word. Hence, researcher has explained in detail the word ‗literacy‘. In this

chapter, researcher has also explained the term ‗literacy‘ was one that has been adopted

by practitioners from a variety of backgrounds to give more description to the term

―literacy‘ and following this, the term, ―financial literacy‖ was defined, and

conceptualized. This chapter has also covered the attempts made by various researchers/

authorities to explain and/or derive a composite definition of financial literacy. This

chapter has also discussed and justified the reason, why financial literacy has gained the

attention of governments, regulatory authorities and policymakers in various countries by

identifying its need and consequences of financial illiteracy. This chapter is concluded

with the scope of the term ―financial literacy‖.

Chapter 2 was aimed at developing theoretical framework for this study. The detailed

literature review was presented and theory building task was carried out in this chapter.

To get an in-depth idea for the topic under study and to support the academic research

base to the research topic, this chapter was divided into two sections. 1) Investors‘ Saving

and Investment Decision, and 2) Financial Literacy and Financial Behaviour. The first

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section of this chapter has begun with the relevance of financial systems to economic

development through the savings-investment process and incorporated the theoretical

framework for this study by summarizing behavioural finance models to explain investor

behaviour, followed by in-depth review of literature on investment motives and factors

that influence the investment decision of investors. This section also included studies

those had measured the association of demographic factors of investors and investment

decisions, importance of risk tolerance ability and need for/ sources of information search

in decision making. The second section of this chapter has included analysis of the

studies conducted in various countries for measuring the financial literacy of their

citizens. This section has also provided the theoretical framework for financial behavior

following the review of literature is presented on various studies those have attempted to

establish the relationship between financial education, financial literacy and various

financial behaviour.

Chapter 3 provides brief outline of the present research study. It gave detailed picture of

Research Methodology. Research gap, objectives and scope of this research study is also

included in this chapter. Exploratory and Descriptive research design was used. The

research has included the explanation about population of the study, sampling techniques,

sample unit, sample and sample size, construction of data collection instrument, different

sources of data used, and data collection methods. The discussion on data analysis

techniques is also presented. The review of literature was also done on available

methodologies to measure the financial literacy on an individual. The merits and demerits

of each method are also discussed, that is followed by the particular methodology

selected by a researcher to measure financial literacy of investors in present study. The

hypotheses framed for this study has concluded this chapter.

Data analysis and interpretation of primary data collected, following the objectives under

study are presented in Chapter 4. Different tools – frequency and percentage analysis,

cross tabulation, chi-square test, paired t-test, factor analysis, binary logistic regression

and simple linear regression is used for data analysis in details to draw a conclusion. The

analysis was divided into three major sections. The first section of this chapter included

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an in-depth analysis of survey responses collected from each respondent towards

performance test that was used to measure financial literacy of investors and to classify

the respondents (investors) into two categories: 1) investors with relatively low level of

financial literacy and 2) investors with relatively higher level of financial literacy. The

second part of this chapter included an in-depth analysis of investment objectives,

existing investment pattern of investors, investors‘ preference towards various investment

alternatives, analysis of informative variables on the basis of investors‘ preference, and

the influence of selected informative variables on investment decision of investors. The

analysis is done by applying factor analysis, identifying the mean score of each factor,

and later applying paired t-test. The factors analysis is also conducted to identify the

factors that may influence the investment decisions of investors. In the third section, the

categories of financial literacy levels, found in the first section of this chapter, are further

used to check the association between each demographic and socio-economic variable of

investors and their financial literacy level. The Chi-square test was used for this purpose.

To assess the combine impact of demographic and socio-economic variables of investors

on their financial literacy level, a binary logistic regression was performed. The chi-

square test also performed to check the association between financial literacy level of

investors and their monthly expenditure to monthly income ratio and similarly, to check

the relationship between financial literacy level of investors and their monthly saving to

monthly income ratio. The correlation and simple regression used to assess the impact of

financial literacy level of investment decision of investors have concluded this chapter.

The present chapter talks about the major findings and its implications in the research

word. The concluding part of this chapter talks on the applicability of this research to

academicians, financial education providers, N.G.O.s and policy maker to promote

financial literacy through financial education.

5.3 Findings of the study

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Findings are the outcomes of an in-depth analysis of data performed in chapter 4. All the

findings are in relation with the objectives of the study and data analysis performed in

this study are mentioned in the following paragraphs.

5.3.1 Findings for the analysis of financial literacy questions

The analysis of total 50 questions to measure financial literacy found that out of

385 respondents, on an average 56.90 % respondents answered correctly. The

minimum score was 20%, while maximum score was 98%.

To measure the financial literacy level of respondents, the respondents‘ total score

was calculated as the percentage of correct answers. The survey responses from

each respondent were used to calculate the median percentage of correct scores

for entire survey. The median of percentage of correct scores achieved by

respondents was calculated, and it was 56.00. The overall scores were grouped

into two categories according to the median percentage of correct scores of all

participants of the survey. Accordingly, a median percentage of correct answers

(i.e. 56.00) of the sample was considered as a base to frame financial literacy

level of the respondents and/or to classify the subgroups. The respondents with

the scores equal to or below median were considered as respondents with

relatively lower level of financial literacy and hence classified into the first

category, i.e. investors with relatively lower level of financial literacy and

respondents with scores above median are considered as respondents (investors)

with higher financial literacy and hence classified in the second category, i.e.

investors with relatively higher level of financial literacy and hence classified into

second category. It was found that out of total 385 respondents, 40.78%

respondents (n=157) scored higher than the median, i.e. 56.00, and hence these

respondents were considered as investors with higher level of financial literacy.

The rest of the 59.22% of respondents (n=228) have scored equal to and/or lower

than median. These investors were considered as respondents with relatively

lower level of financial literacy and hence classified as lower financially literate.

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On the basis of percentage of correct answers given by the respondents for each

question, sorting was done and rank was given to each subject question. Analysis

shows that for basic financial literacy, the respondents earned highest score on the

question of numeracy (80.78%, n=311), suggesting that investors know this

concept very well. Nine other subject questions had scores higher than the

median. In the ascending order, these subjects are ‗consumer rights and

responsibility‘ (80.26%, n= 309), ‗concept of know your client‘ (KYC) (78.96 %,

n=304), ‗interest compounding‘ (76.62%, n=295), ‗functioning of stock market‘

(73.25%, n=282), ‗relationship of investment time horizon and fluctuation in asset

value‘ (71.43%, n=275), ‗diversification‘ (69.09%, n=266), ‗inflation‘ (68.83%,

n=265), ‗risk-return trade off and risk-return trade off‘ (65.71%, n=253) and ‗risk

return trade off of two assets‘ (65.19%, n=251).

Under the basic financial literacy test, the subject questions where the respondents

scored less than the median are concept of ‗investment‘ (51.95%, n=200),

‗financial worth‘ (50.13%, n=193), ‗concept of risk‘ (48.31%, n=186),

‗relationship between investment time horizon and asset growth‘ (47.01%,

n=181), ‗personal finance‘ (42.08%, n=162), ‗time value of money‘ (41.56%,

n=160), ‗relationship between interest and asset prices‘ (41.30%, n=159),

‗regulatory as a part of market structure‘ (27.09%, n=107), ‗concept of asset

al.location‘ (27.53%, n=106) and ‗disposable income‘ (22.60%, n=87).

The result of analysis of advanced financial literacy test shows that respondents

scored highest score on the product i.e. fixed deposits (74.89%, n=865/1155),

followed by insurance plans (62.86%, n=968/1540), mutual funds (60.69%,

n=701/1155), national savings certificates (60.00%, n=693/1155), preference

shares (56.23%, n=433/770). The respondents are less literate on the investment

alternatives, i.e. Equity shares (54.81%, n=633/1155), employee provident fund

(51.00%, n=589/1155), Post office monthly income schemes (50.22%,

n=580/1155), public provident fund (49.87%, n=576/1155) and Debentures and

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Bonds (48.74%, n=563/1155), which is far from median score and concluded that

respondents are less financially literate/knowledgeable on these investment

alternatives.

By analysis of mean score of preferred investment alternatives, it was found that

the bank deposits are highly preferred by the investors (mean score 5.96),

followed by precious metals (gold and silver) (mean score 5.78) and insurance

and pension plans (mean score 5.66), while investment in shares are found to be

the least preferred by the investors having mean score of 3. 54.

5.3.2 Findings for analysis of existing investment pattern, investment objectives and

preferences for various investment alternatives

With regard to existing investment pattern, out of 385 respondents, 318

respondents have invested in bank deposits, followed by the insurance and

pension plans (n = 299). 279 respondents have invested in precious metal (gold

and silver), while 157 respondents have invested in mutual funds. 148, 134 and

122 respondents have invested in shares, post office saving schemes and real

estate respectively while, only 33 investors have invested in bonds and

debentures.

For ranks given to investment objectives, 35.32% (n=136) of the respondents

have given first rank to saving of income tax as an investment objective, while

only 4.16% (n=16) have given the seventh rank to the same investment objective.

Analysis of the data shows that 72.99% (n=281) respondents have given the

seventh rank to gift/donation/vacation/pilgrim as an investment objective, 21.82%

(n=84) respondents have given second rank to child‘s marriage/child‘s

education/social ceremony. 12.21% (n= 47) respondents have given first rank to

secured retirement and safeguarding against inflation/capital appreciation. With

regard to buying/improving home and meeting unexpected needs only 9.87% (n=

38) and 14.55% (n=56) respondents have given first rank respectively.

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By analysis of mean score of investment objectives, it was found that two

investment objectives i.e. saving of income tax and meeting unexpected financial

needs have secured the highest mean score i.e. 4.78, which is followed by the

secured retirement (mean score 4.63) and Child‘s marriage/ child‘s

education/social ceremony (mean score of 4.43). The investment objective Gift/

donation/ vacation/ pilgrim has secured the lowest mean score of i.e. 1.58.

With regard to ranks given to investment alternative, as per the preference of

respondents, out of total, 38.96% (n=150) respondents have given the first rank to

bank deposits as the most preferred investment alternative. The second and third

most preferred investment alternative are precious metals (gold and silver) and

insurance and pension plans preferred by 15.32% (n=59) and 14.03% (n=54)

respondents respectively, accordingly the second and third rank were given to the

precious metal and insurance/pension plans. While 37.66% (n=145) respondents

have given the eighth rank to bonds and debentures, hence, bonds and debentures

are considered to be the least preferred investment alternatives by the respondents.

5.3.3 Findings for analysis of preference of investors towards preferred source of

information while investment

With regard to information search, on the basis of mean score of sixteen variables

as a preferred source of information, certified financial planner (4.20) is found to

be the most preferred source of information, followed by opinions from the

present investors (4.09), conversation and exchanges of views with company

executives and sector experts (3.98) and distributer/ agents of financial

products/services (3.93) respectively.

On the basis of mean scores of sixteen variables for information search, the three

least preferred informative variables include prospectus of a company (3.41),

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published reports of the research agencies (3.47) and corporate forecast prepared

by independent investment companies (3.51).

On the basis of mean scores of selected variables for information search, the three

least preferred variables include corporate forecast prepared by independent

investment company, rating agencies‘ reports and publication in financial Press,

newspapers and electronic media, each having a mean score of 3.51, 3.57 and

3.62 respectively.

On the basis of mean scores of selected variables for information search, it was

found that the three most influencing informative variables on investment

decision were rating agencies‘ reports (mean score 4.17), annual reports (4.09)

and conversation /exchanges of views with company executives and sector

experts (mean score 3.97).

Among the selected variables of preference for information search, it was found

that the three least influencing informative variables in the investment decision

are corporate forecast prepared by independent investment company, present

investors and conversation/exchanges of views with professional colleagues, each

having a mean score of 2.48, 2.88 and 2.94 respectively.

The gap analysis was also performed. Gap in the mean score was identified by

subtracting the mean score of variables for which responses given on the basis of

influence of these variables on investment decision form the mean score of

variables for which responses given on the basis of preference towards a variable

as a source of information. The three most positive gaps found for the variables

present investors, corporate forecast prepared by independent investment

company and conversation/exchanges of views with professional colleagues.

These high gaps indicate that the preference of respondents towards various

variables of information is very high as compared to the influence derived from

this.

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To know the difference between the preference and influence of informative

variables on investment decision, the paired t-test was performed. It was found

that only for two pairs, the significance value is greater than 0.05 and that is for

the variables 1. Conversation/exchanges of views with company executives and

sector experts and 2. Financial advisors/brokers and analyst‘s recommendation.

For these two variables, null hypothesis was not rejected and concluded that for

conversation/exchanges of views with company executives and sector experts and

financial advisors/brokers and analyst‘s recommendation, there is no difference

between preference for these informative variables and their influence on

investment decision under study at 5% level of significance. For rest of variables,

the difference between preference for the informative variables and their influence

on investment decision is statistically significant at 5% level of significance.

Factor analysis was used to convert more number of variables into less number of

factors. The factor analysis was performed for sixteen variables preferred by

investors as source of information while making investment decision. Before

performing factor analysis the reliability of sixteen informative variables was

checked with Cronbach‘s alpha and was 0.708. The Bartlett‘s test of sphericity

was significant with the value of 0.000. The Measure of Sampling Adequacy was

checked with K.M.O. value, which shows 0.664. These permitted researcher to

proceed further to run factor analysis. With the help of factor analysis, five factors

were extracted from fourteen variables (as two variables out of sixteen variables

were removed due to their communalities were lower than 0.500) under study.

67.12% of the total variance was explained by these extracted factors. These five

factors are named as ―Published Operational Information‖, ―Independent

Information‖, ―Advocate Recommendation‖, ―Accessibility Information‖ and

―Performance Forecast‖.

The mean score of each of above extracted factor was also found. It was found

that for factor 2 (i.e. Independent Information) and factor 4 (i.e. Accessibility

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Information), the mean score is highest, i.e. 3.89. This indicates that these two

factors are the most preferred by investors to collect the information, which is

followed by the mean score of factor 3, i.e. advocate recommendation, for which

the preference mean score is 3.77. The least score is for factor 5, i.e. 3.51. This

indicates that performance forecast is the least preferred by the respondents to

gather the information for their investment decision.

5.3.4 Findings for Factor Analysis performed for variables influencing Investment

Decision of Investors

The factor analysis was also performed for forty four variables, influencing

investment decision of investors. Before performing factor analysis the reliability

of these forty four variables influencing investment decision of investors was

checked with Cronbach‘s alpha and it was found 0.794. The Bartlett‘s test of

sphericity was significant with the value of 0.000. The Measure of Sampling

Adequacy was checked with K.M.O. value, which shows 0.690. These permitted

researcher to proceed further to run factor analysis. With the help of this factor

analysis, nine factors were extracted from twenty nine variables (as fifteen

variables were removed due to their communalities lower than 0.500) under

study. 62.10% of the total variance was explained by the extracted factors. These

factors are ―Personal Financial Need‖, ―Accounting, Business And Financial

Information‖, ―Economic and Regulatory Environment‖, ―Operational Feedback‖,

―Advocate Recommendation‖, ―Overall Group Performance‖ , ―Credit Features‖

And ―Personal Inclination‖ and ―Monetary Expectations‖.

The grand value of mean score was also found for these extracted factors. It was

found that for factor 1: ―Credit features‖, the mean score is highest, and it is 4.07.

This indicates that this factor is the most influencing factor on investment

decision of investors. This factor is followed by the mean score 4.03 of factor 9,

i.e. Monetary expectation.

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5.3.5 Findings for the Cross –tabulation and Chi-square test performed to know

association between each demographic and socio-economic variable of investors and


With regard to age of investors and their financial literacy level, the chi-square

test found that a significant association between these two variables. For current

study, the strength of this association is found to be 59.40% as shown by

Cramer‘s V. The cross tabulation shows that out of total investors fall under both

the extremes (for age group of 18 years to 25 years ( n= 89), 26 years to 35 years

(n=76) and 56 years and above (n=49)), out of which majority of the investors

possess lower level of financial literacy (i.e. for the age group of 18 years to 25

years ( n= 85, 95.5%), 26 years to 35 years (n=65, 85.53%) and 56 years and

above (n=27, 55.10%)).These findings are consistent with Chen & Volpe (1998),

Volpe & Chen (2009), ANZ Bank (2003), Commonwealth Bank (2004), Lusardi

& Mitchell (2009), OECD (Australia) Studies (2005).

Cross tabulation performed for two variables, investors‘ gender and their financial

literacy level found that as compared to male investors, female investors possess

much lower level of financial literacy. This finding is consistent with the studies

done by Chen and Volpe (1998), Volpe and Chen (2002), Lusardi and Mitchell

(2009). Chi-square result also found a significant association between investors‘

gender and their financial literacy level. This finding is consistent with H. A.

Hassan and A.A. Bin Kali (2009). For these two variables, Cramer‘s V value is

30.8%, which shows that there is a low level of association between these two

variables.

Chi-square test performed to know association between investors‘ education and

financial literacy level found no significant association between the respondents‘

education and their financial literacy level. It may be concluded that ―educated

does not mean that to be financially literate‖. The cross tabulation performed for

these two variables shows that out of total investors who are non-graduate

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(investors with primary education (n=24), investors with secondary education

(n=45), investors with higher secondary education (n=46) and those with diploma

(n=29)), majority of them possess lower level of financial literacy. (i.e. investors

with primary education (n=18, 75.00%), investors with secondary education

(n=22, 48.89%), investors with higher secondary education (n=30, 65.22%) and

those with diploma (n=18, 62.07 %)). This finding is consistent with the findings

of Volpe & Chen (2002), ANZ Bank Study (2003), Commonwealth Bank Study

(2004).

Chi-square test performed to check association between monthly income of

investors and their financial literacy level found a statistical significant

association between monthly income of investors and their financial literacy level.

These findings are consistent with previous study H. A. Hassan and A. A. Bin

Kalli (2009). The strength of the association between these two variables is found

to be 30.4 % as measured by Cramer‘s V. The cross tabulation performed for

these two variables found that those investors whose monthly income is less than

Rs. 10,000 (n=95), out of which, 84.21% (n=80) investors possess lower level of

financial literacy. With regard to the investors whose monthly income is more

than Rs. 25,001 (n=44), out of which 77.27% (n=34) possess higher level of

financial literacy. The researcher may conclude that the investors with lower

monthly income demonstrate lower level of financial literacy than those with

higher monthly income. These finding is consistent with the findings of ANZ

Bank Study (2003), OECD Studies (2005), Beal & Delpachitra (2003) and

Commonwealth Bank Study (2004).

Chi-square test was performed to check association between investors‘ stage of

life cycle and their financial literacy level. The result found that these two

variables do have statistical significant association with each other. These

findings are consistent with the earlier studies done by Chen and Volpe (1998).

The strength of association between these two variables, as measured by Cramer‘s

V, is found to be 30.4%. The cross tabulation performed for these two variables

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also shows that the investors falling under the categories of young single (n=67)

and young married without children (n=67), of which the higher number of

investors (for young single 83.58% (n=56) and for young married without

children 71.64% (n=48)) possess lower level of financial literacy than those who

are married with children and/or older married. This finding is consistent with the

findings of Lusardi & Mitchell (2009), ANZ Bank Study (2003), OECD studies

and commonwealth Bank Study (2004).

Chi-square test performed to know the association between type of employment

structure of investors and their financial literacy level found that there is no

association between type of employment structure of investors and financial

literacy level. This finding is consistent with the findings of previous study of H.

A. Hassan and A. A. Bin Kalli (2009).

With regard to type of workplace activity of investors and their financial literacy

level, the results of cross tabulation shows that out of total investors engaged in

finance related work activity (n=133), out of these majority of investors, i.e.

72.18% (n=96), possess higher level of financial literacy. While out of total

investors engaged in non-finance related workplace activity (n=242), 75.21%

(n=182) possess lower level of financial literacy. It is concluded that the investors

who are engaged in finance related work place activity possess higher level of

financial literacy than those who are not engaged in finance related work activity.

The results of Chi-square test found a statistical significant association between

type of workplace activity of investors and their financial literacy level. These

findings are consistent with previous study of H. A. Hassan and A. A. Bin Kalli

(2009). The strength of the association between these two variables is 46.70%, as

indicated by Cramer‘s V.

The cross tabulation of two variables investors‘ years of work experience and

their financial literacy level found that those having a work experience of less

than five years posses lower level (n=71), of which majority of investors (n= 57,

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80.88%) possess lower level of financial literacy. This finding is similar and

consistent with the finding of Chen and Volpe (1998). Chi-square test was

performed to know association between investors‘ years of work experience and

their financial literacy level found a statistical significant association between the

investors‘ years of work experience and their financial literacy level. This finding

is consistent with the findings of Beal & Delpachitra (2003). The degree of the

association between these two variables is found to be 28.6%, as indicated by

Cramer‘s V.

The cross tabulation performed between two variables, i.e. investors‘ years of

investment experience and their financial literacy level shows that those having

investment experience of less than one year (n=70), of these majority of investors

(n= 69, 98.57%) possess lower level of financial literacy. The Cross tabulation

Table also shows that as the years of investment experience increases, the level of

financial literacy also increases. It was found that out of total investors who have

invested for the last more than 10 years (n=78), of these, majority of investors

(n=57, 73.8%) possess higher level of financial literacy. The Chi-square test was

performed to know association between investors‘ years of investment experience

and their financial literacy level. The result of this test shows a statistical

significant association between the investors‘ years of investment experience and

their financial literacy level and the strength of this association between these two

variables is 62.3%, as indicated by Cramer‘s V.

Similarly, the cross tabulation performed for two variables, i.e. number of times

investors shop around/make inquiry and their financial literacy level shows that

out of total investors who shop around/make inquiry on an average for more than

6 times (n=36), out of these majority of investors (i.e. n=32, 88.89% of investors)

possess relatively higher level of financial literacy as compared to those who do

not shop around at all (n=87), of these majority of investors (n=81, 93.10%)

possess lower level of financial literacy. The Cross tabulation also shows that as

the frequency of number of times investors shop around/make inquiry increases,

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the level of financial literacy also increases. The Chi-square test was also

performed to know association between these two variables, i.e. number of times

investors shop around and their financial literacy level. The result of this test

shows a statistical significant association between the number of times investors

shop around/make inquiry and their financial literacy level and the strength of the

association between these two variables is 68.30%, as indicated by Cramer‘s V.

The results of chi-square test performed to know the association between risk

tolerance level of investors and their financial literacy level show a statistical

significant association between risk tolerance level of investors and their financial

literacy level. The strength of the association between these two variables is found

to be 15.60%, as indicated by Cramer‘s V.

5.3.6 Findings for Logistic Regression performed to assess the combine impact of

Demographic and Socio-economic variables of Investors on their Financial Literacy

Level

The logistic regression was performed to study the impact of demographic and

socio-economic variables of investors (i.e. gender, age, education, income, stage

in family life cycle, monthly income, employment structure, workplace activity,

number of years of work experience, number of years of investment experience,

risk tolerance level, number of times investors shop around) on their financial

literacy level. Logistic regression shows that a financial literacy level of investors

varies with their demographic and other characteristics. A test of final model

against constant model is found to be statistically significant, indicating that the

predictors as a set reliably distinguished between higher and lower level of

financial literacy (chi square = 420.876, p < 0.05, with df =39). Nagelkerke‘s R2

is found to be 0.897 indicated a strong relationship between prediction and

grouping. The overall prediction success was 95.60% (97.8% for lower level of

financial literacy and 92.4% for higher level of financial literacy). The Wald

criterion demonstrated that except education, years of work experience and risk

315

tolerance level, all the predictors are important predictors to predict financial

literacy level.

5.3.7 Findings for the Cross –tabulation and Chi-square test performed to know

association between each financial literacy level of investors and their monthly

expenditure to monthly income ratio and monthly saving to monthly income ratio

To check the association between financial literacy level of investors and their

monthly expenditure to monthly income ratio, the chi-square test was performed.

The results of this test found a significant association between financial literacy

level of investors and their monthly expenditure to monthly income ratio and the

strength of the association between these two variables is 21.10%, as indicated by

Cramer‘s V.

Similarly, to know the association between level of financial literacy of investors

and their monthly saving to monthly income ratio, chi-square test was performed.

The chi-square test shows a significant association between these two variables

and the strength of this association is found to be 64.40%, as indicated by

Cramer‘s V.

5.3.8 Findings of correlation and regression performed to assess the impact of

financial literacy level of investors on their investment decision

To study the impact of financial literacy level of investors on their investment

decision, all 9 factors extracted from factor analysis are taken individually as well

as sum of all investment factors extracted from factor analysis is taken as

dependent variable and financial literacy level as an independent variable. The

correlation and simple linear regression method was used. For individual variable,

it was found that financial literacy level does have positive correlation with the

factors 1 ‗Personal Financial Need‘, Factor 5 ‗Advocate Recommendation, and

Factor 6 ‗Overall Group Performance‘, and regression analysis found that

316

financial literacy level does have its significant impact on above mentioned

factors. Correlation analysis also found that financial literacy level does not any

correlation with Factor 2 ‗Accounting, Business and Financial Information‘,

Factor 3 ‗Economic and Regulatory Environment‘, Factor 4 ‗Operational

Feedback, Factor 7 ‗Credit Features‘, Factor 8 ‗Personal Inclination‘ and Factor 9

‗Monetary Expectation‘.

For assessing the impact of financial literacy level on sum of investment decision

factors, the correlation and regression analysis is performed. It was found that

financial literacy level does have positive correlation with sum of investment

factors. The regression analysis found that financial literacy does have a statistical

significant impact on sum of investment decision factors. Thus, it may conclude

that a financial literacy level of investors does have a statistical significant impact

on their investment decision.

5.4 Conclusion

Based on data analysis some conclusions are presented as under.

All the respondents (investors) have parked their savings in various

investmentalternatives, though majority of the respondents (investors) possess lower

level of financial literacy. This shows that all the investors do not understand the

basics of investments and its calculation.

From the analysis of financial literacy questions, it is also found that the majority

investors are less financially literate on some of subjects of basic financial literacy

and advanced financial literacy and even some of them do not understand the

important concepts at all.

With regard to demographic and socio-economic profile of respondents and financial

literacy, it was found that females possess lower level of financial literacy, as

317

compared to males. It was also found that investors on the basis of two extremes of

age i.e. 18 to 35 years and 56 years and above possess a lower level financial

literacy. On the basis of monthly income group of respondents, it is found that the

respondents falling under lower income groups possess a lower level of financial

literacy.

It is also concluded that for respondents with higher monthly income, higher number

of years of investment experience, and those who shop around maximum number of

times/ make maximum number of inquiries while investing, possess comparatively

higher level of financial literacy than others.

With regard to investment objective, for majority of investors (respondents), the first

investment objective is saving of income tax and meeting unexpected financial

needs.

It is also concluded that majority of the investors (respondents) invest in and/or

prefer conventional savings/investment alternatives to park their savings, which

renders them unable to cope up with the rate of inflation in a long run.

Further, it is also found that financial literacy does have statistically significant

impact on investment decision. It may be concluded that financial literacy may

empower the investors to make investment decision.

With regard to the relationship between financial literacy and financial behavior, it

was found that financial literacy leads to controlled spending behavior and

encouraged saving behavior and also have a significant impact on investment


318

5.5 Recommendations

Increase in the life expectancy, changes in pension agreement and transfer of risk,

increase in an individual‘s responsibility, financial product and services Innovation,

globalization, privatization and deregulation of financial services industry, multifaceted

features of financial products, technological changes and market innovations have sought

the attention of educators, community groups, businesses, government agencies,

organizations, non government organizations, policy makers and regulatory authorities.

Based on findings of the present study, the researcher suggests the financial education

providers, investors and policy makers and regulatory authorities to promote financial

literacy.

5.5.1 For Policy makers and regulatory authorities

More emphasis on financial education should be given to college students as there is

a low level of literacy prevalent amongst the age group 18-25 and 26-35 years. Due

to lack of financial literacy, they may misallocate the private wealth, which may

restrict them to achieve their financial objectives in long run. Since college students

are the most vulnerable to be trapped in debt, Policy makers can design financial

education material focused on Personal finance.

With respect to retirees or the investors having the age of 56 years and above, this

group should be targeted with an objective to learn them the importance of

retirement planning as a part of financial planning so that these investors can teach

the importance of retirement planning to their children, if they have not done yet. In

line with the same, the awareness of future retirees about the need to assess the

financial adequacy of their current public or private pension schemes and to take

appropriate action when needed should be encouraged.

319

It is recommended that females should be targeted to provide financial education and

to empower and encourage them or to make them realize the importance of their

role/participation in investment decision making at household level.

There is a need to start the financial education program at an earlier stage in the life

cycle of people as that will ensure that the habit of savings and proper money

management and investment is ingrained into them right from their childhood.

There is a need to consider including financial education/ money management as a

specific subject in the syllabus at the primary and secondary school level.

The investors with lower income and those who work with non-financial services

industry mostly possess low level of FL. there is even more need to teach these

people about money management so that their limited income (monetary resource) is

put to optimum use. There is a need to provide financial education to these people at

their workplace.

To empower the investors on the subject of financial literacy, the issue of financial

literacy should be taken either as a policy perspective or as a pragmatic perspective

5.5.2 For Investors

Investors should start showing interest in financial education.

Females should start taking more initiative in financial matters and should be more

assertive in family financial matters

Schools, colleges, universities should introduce the syllabus of financial education to

enhance the financial literacy of their students. A common learning goal and

financial language should be established for financial literacy education across the

various masses of society, subject matter and levels. The development of financial

320

skills and knowledge should ideally begin at home and be continued in school,

college, workplace levels and the community as a whole. It should be easily and

widely accessible to all sectors of the community at all stages of the lifecycle.

At workplace, employer should encourage the workplace financial education

programmes.

The NGOs working for social up-liftment of women must ensure that the financial

education should be provided to them for their economic up-liftment.

5.5.3 For Financial Education Providers

Should provide the financial education as an ―information‖ and ―instruction‖ not as

an ―advise‖.

Further, it should be provided in fair and unbiased manner.

Companies should also emphasis on developing financial literacy of the community

by providing financial education to various masses as a part of Corporate Social

Responsibility.

For promoting and coordinating financial education, the national, regional, local public

and private initiatives should reach the population and raise awareness of the population

about the need to improve their understanding of financial risks and ways to protect

against financial risks through adequate savings, insurance and financial education.

Financial education complements the important aspects like greater transparency, policies

on consumer protection and regulation of financial institutions. Financial literacy should

be on a common structure and a common approach so that it can be spread in a

comprehensive manner. These efforts should aim at empowering consumers to

understand and select the financial products and services that best suit their needs, goals

321

and personal circumstances. The overall efforts by regulatory authorities, N.G.O.s and

community groups should be structured in the direction to enable the individuals to

develop the ability to make informed judgments, to be able to identify financial products

and services that address their needs, to take effective decisions regarding the use and

management of their money and to avoid to be a victim of bad selling.

However, financial literacy can only ensure individuals are informed and empower to

make financial decisions, it cannot ensure that 'right' decision is actually made, because,

individuals do not always make decisions based purely on economic rationality, personal

circumstances and social factors, which are beyond the control of an individual are also

considered while taking the decisions.

5.6 Limitations of the study

Care and attention has been taken to ensure that the research was designed and conducted

to optimize the ability to achieve the objectives of the research. However, researcher

sometimes was unable to conduct study with zero defects due to personal resources

constraints in terms of time, manpower and money, which results in error in data

collection and analysis. Some other limitations of this study are mentioned below.

The method adopted for primary data collection was non-probability convenience

sampling method, which does possess it own limitations, hence these limitations

automatically applies to the study.

The bias in respondents‘ views can‘t be ignored.

The investors who have just started to make investment, and those who make

investment decision on the basis of others‘ recommendation, without any analysis of

their own, it was difficult for them to answer the questions about financial literacy

and to give rating.

322

In this study, all the respondents (i.e. retail individual investors) were from urban

areas of Gujarat state. It may be possible that the views of respondents from rural

areas turn out to be different from the respondents belonging from urban areas.

While every care has taken to use, both primary and secondary sources of information

and efforts have been made to provide generic conclusions which would cover all

possible situations, still it needs to be mentioned that the conclusion of this study may

not be applicable uniformly in all situations and therefore, they would need to be

applied taking into account the prevailing circumstances in a particular case.

5.7 Scope for further research

No research in any subject can be complete in itself. In this study, an attempt was made

to explore the financial literacy level of investors and its impact on investment decision

among the investors of Gujarat State. The study is limited up to these two outcomes.

However, more areas can be explored for further research taking the present study as a

base. Some of the scopes for further research are as under:

As mentioned in the limitations, this study is based on the responses of retail

individual investors of urban areas in Gujarat state. One can expand the study by

including rural population of the Gujarat state. One can also perform a comparative

study on responses collected from rural investors and responses collected from urban

investors.

Research is performed on the basis of views collected from retail investors. One can

perform or expand this study by collecting the responses from HNIs (High Networth

Investors).

In the present study, the impact of financial literacy on investment decision of

investors is examined. There is enough scope to perform the research by examining

the impact of financial literacy on stock market participation, portfolio diversification,

323

individual saving behavior, individual spending behavior, overall financial behavior

as well as readiness to participate in retirement planning.

Nowadays, SHG members are empowered through financial education and their

socio-economic status is enhanced through micro-finance activities. Hence, one can

also perform this study by collecting the responses only from SHG members.

At broad spectrum, one can also perform the research on role of financial literacy and

demand elasticity in promoting a sound financial systems.

The present study is performed in the state of Gujarat. One can also perform the study

in other parts of India and/or at national level as a whole. Also, comparison of two or

more states‘ data can be possible.

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Appendix

347

ANNEXURE I

Dear respondent,

Season’s greetings to you,

Section A: Basic Financial literacy

1. Which of the following is correct? Investment can be made by

A. Government B. Households C. Business

Only A & B Only B & C

Only C & A All of above None of above

2. Financial worth: Suppose you have the total assets of Rs. 20,000; out of which investment comprising of Rs.

10,000; on the other hand you are owing total liabilities/debt of Rs. 10,000, then your financial worth will be

calculated by:

Total assets minus total liabilities Total investment minus total debt

Total worth of all the personal assets Don‟t know

3. Disposable income: Suppose your monthly income is Rs. 10,000, on which you are supposed to pay tax of

Rs. 1000, and your monthly saving is Rs. 1,500, what will be your disposable income differs from:

Monthly income = disposable income Personal taxes Personal saving

Personal consumption expenditure None of above Don‟t know

4. Out of following, which account cannot be open by layman individual?

Saving account Current account DEMAT account

Fixed Deposit account Recurring Deposit account Don‟t know

5. Numeracy: Suppose you have Rs. 100 in a saving bank account, earning an annual interest rate of 2 % under

simple interest rate method. After five years how much do you think to you would have in the account if you

have left the money to grow?

More than Rs. 102 Less than Rs. 102 Exactly Rs. 102

None of above Don‟t know

6. Interest Compounding: Suppose you had Rs. 100 in a saving account and the interest rate is 20 % per year

and you never withdraw money or interest payments. After 5 years, under compounding how much would you

have on this account in total?

More than Rs. 200 Exactly Rs. 200 Less than Rs. 200

None of above Don‟t know

7. Inflation: Imagine that the interest rate on your savings account was 1% per year and inflation was 2% per

year. After 1 year, how much would you be able to buy with the money in this account?

More than today Exactly the same Less than today Do not know

8. Time value of money: Assume a friend inherits Rs. 10000 today and his sibling inherits Rs. 10000 3 years

from now. Who is richer because of the inheritance?

My friend His sibling They are equally rich Do not know

I, Harsha Jariwala pursuing Ph.D. on “To study the level of financial literacy and its impact on investment

decision: An in-depth analysis of investors of Gujarat state”. Your valuable feedback will be helpful to me to

accomplish my study successfully. I will be thankful to you, if you will answer the given questions and provide

the comment for required information that best suit to your knowledge and information. I assure you; the

information given by you will be used only for the study purpose and will be kept confidential.

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9. Functioning of Stock market: Which of the following statements describes the main function of the stock

market?

The stock market helps to predict stock earnings;

The stock market results in an increase in the price of stocks

The stock market brings people who want to buy stocks together with those who want to sell stocks

None of the above Don‟t Know

10. Diversification: When an investor spreads his money among different assets, does the risk of losing money:

Increase Decrease Stay the same None of above Don‟t know

11. Risk-return trade off: Buying a single company‟s stocks usually provides safer return than a stock mutual

fund.

True False None of above Don‟t know

12. Risk: The presence of risk means that

Investors will lose money.

More than one outcome is possible. .

All of above None of above Don‟t know

13. Risk-return trade off of two assets: Stocks are normally riskier than bonds.

True False Don‟t know None of above

14. Relationship between investment time horizon and asset growth: Considering a long time period (for example 10 or 20 years), which asset normally gives the higher return among the specified below?

Saving account Bonds Stocks

None of the above Don‟t know

15. Investment time horizon and fluctuation: Out of following; normally which asset displays the higher price

fluctuations over time?

Saving account Bonds Stocks

None of the above don‟t know

16. Asset Allocation: In Asset allocation the investor involves in

A. decision to allocate his corpus between a risk-free asset and a risky asset.

B. decision his corpus among different risky assets.

C. considerable security analysis.

None of the above don‟t know

17. Relationship between interest and asset prices: If interest rate falls, what should happen to bond prices?

Rise Fall Stay the same Don‟t know

18. Consumer rights & responsibility: If a person keeps PIN number of ATM card on a piece of paper in a wallet

along with ATM card. If the wallet is stolen, and card and PIN no. are used to take money from an account,

who will be responsible for money lost?

A bank only A card holder only both of them Don‟t know

19. Regulatory body as a part of market structure: Out of following which is not the regulatory authority.

SEBI IRDA RBI AMFI

None of above All of above Don‟t know

20. KYC: “Know your customer” (KYC) is a document, which is used for customer/client identification process.

True False Don‟t know

Total Score: /20

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Section B- Advanced Financial Literacy

Following are the statements regarding the features of various investment alternatives available for individual investors.

On the basis of your understanding and knowledge about the investment alternatives answer the following (Tick any

one). There is no mark.

Total Score: /30 = _____/50

True False DK

Fixed Deposits

1. It is a lump sum amount in the bank at a certain rate of a interest for a fixed period of time.

2. Rate of interests offered on fixed deposits by various banks are same.

3. The rate of interest offered on fixed deposits is calculated under compound interest method.

National Savings Certificates (NSCs)

4. It is a long term risk free investment.

5. NSCs are issued by the corporate only.

6. Interest rate is constant and calculated twice in a year.

Public Provident Fund (PPF)

7. There is no minimum and maximum limit of investment made in PPF per year.

8. There is no lock in period for PPF.

9. The amount deposited during the year is eligible for tax deduction irrespective of the sum.

Employee Provident Fund (EPF)

10. Employee provident fund is applicable to salaried employees only.

11. Employee can invest the amount higher than mandatory contribution in EPF.

12. The whole amount contributed by employer is deposited in employee‟s EPF account.

Equity Shares

13. A equity shares represent the ownership of a company.

14. The return that the owner of a share receives is known as earning per share.

15. Dividend is paid on the basis of market price of the share.

Preference Shares

16. Preference shareholders get the preference over the equity shareholders at the time of dividend distribution.

17. Preference shareholders do not get the preference over the equity shareholders at the time of liquidation of a company and distribution of sales proceed.

Mutual Fund

18. When an investor invests in mutual fund, he receives units in return.

19. The price of a mutual fund unit is known as Net Asset Value.

20. Mutual funds pay a guaranteed rate of return which depends on their past performance.

Debentures and Bonds

21. Investment in infrastructure bonds is not eligible for income tax benefits.

22. The return on bonds and debentures is remain same over the investment period.

23. If a somebody buys a bond of a firm, then he owns a part of the same firm.

Post Office Monthly Income Scheme(POMIS)

24. Investment in POMIS is not guaranteed by the Government of India.

25. There is no lock in period.

26. The premature withdrawal does not carry any penalty charges after one years of investing in POMIS.

Insurance Policy

27. All the types of illnesses are covered under the life insurance.

28. Life insurance policy is transferrable in nature.

29. The life insurance premium payments do not enjoy the tax benefits under section 80 C.

30. The amount received on the maturity of life insurance policy is taxable.

350

Section C: Investment Decision: Questionnaire

1. Do you invest your saving in any of the investment alternative available?

Yes (Go to question 2) No (Go to question 4)

2. Out of following, in which saving and/or investment alternative you have invested in?

Post Office Saving Schemes (POMIS/NSC/KVP/PPF etc.) Insurance and Pension Plans

Shares Mutual Funds

National Saving Certificates/KVP Debentures and Bonds

Real Estate Precious Metals (Gold & Silver)

3. If you have „n‟ amount of corpus, available with you, out of following, in which investment alternative would you like

to invest? (Rank them, where 1 is the most preferred)

Post Office Saving Schemes (POMIS/NSC/KVP/PPF etc.) Insurance and Pension Plans

Shares Mutual Funds

National Saving Certificates/KVP Debentures and Bonds

Real Estate Precious Metals (Gold & Silver)

4. Out of following reasons which restrict you to make the investment? Rank them. (Go to section D)

I prefer to have complete liquidity on my hands. There is no need to make an investment.

I don‟t possess investment knowledge I don‟t have enough money for investment.

I did never consider making an investment. I never have a time to arrange for investment.

I don‟t see any benefits of doing so. I don‟t trust the information given by the advisors/ company.

I find it all to confusing. For me, all the investment alternatives are too risky

Put off by high fees charged by advisors and companies.

.

5. Following are the objectives of investment. (Rank them, where 1 is the most preferred)

Saving income tax Children marriage/ Social ceremonies/ Child‟s education

Buying/ improving/ a home For secured retirement

Gift/Donation/ Vacation/Pilgrims To meet unexpected financial contingencies

Safeguard against inflation/ Capital appreciation

6. Before investing your savings, I prefer to collect the information from.

Not

Preferred

Least

Preferred

Neutral Preferred Most

Preferred

1 Certified Financial Planner

2 Annual reports of the company

3 Prospectus of a company

4 Company‟s website

5 Distributers/agents of financial product

6 Rating agencies‟ reports

7 Company‟s telephone representatives

8 Family members

9 Friends and relatives

10 Conversation/exchanges of views with professional colleagues

11 Publication in the financial press, news papers & electronic media

12 Conversation/ exchanges of views with company executive and sector experts

13 Corporate forecast prepared by independent investment company

14 Published reports from research agencies

15 Opinions from existing investors of various instruments

16 Financial advisors/Broker and analyst‟s recommendation

351

7. Following are the variables that influence my investment decision, Rate them.

Least influence

Influence Neutral Significantly Influence

Most Significantly

Influence

1. Condition of financial statement

2. Expected corporate earning

3. Past performance of the firm(in terms of profit and return given to investors)

4. Company‟s position in the industry

5. Insiders‟ information

6. The result of fundamental analysis

7. The result of technical analysis

8. Expected return on investment

9. Feeling for a company‟s products or services

10. Perceived ethics of company

11. Political party affiliation

12. Contribution of a firm towards social causes

13. Coverage in the press

14. Recent price movements in a firm‟s stock/NAV

15. Statements from politicians and governmental officials

16. Fluctuations/developments in the indices of the major market

17. Current economic indicators

18. Reputation of a company in the domestic market

19. Reputation of a parent company or sister concern

20. Environmental Record

21. Market Capitalization of company

22. Conversation/exchanges of views with professional colleagues

23. Publication in the financial press, newspapers and electronic media

24. Conversation/ exchanges of views with company executive and sector experts

25. Studying the portfolio investments of other market players

26. Corporate forecast prepared by independent investment company

27. Economic forecasts by research institutions

28. Study of Annual Reports

29. Opinions from family members

30. Opinions from friends and relatives

31. Opinions from existing investors

32. Financial advisors/Broker and analyst‟s recommendation

33. Opinion of Credit Rating agencies‟ analysis

34. Diversification needs

35. Liquidity associated with investment

36. Availing the benefit of income tax deduction

37. Risk-return trade off

38. Minimizing risk

39. Ease of obtaining borrowed fund

40. Preferred investment time horizon

41. Safety associated with investment

42. Affordable minimum investment amount

43. Ease in Liquidity

44. Guaranteed return

352

8. Given below the small questions to understand what sort of investor you are. Kindly tick one for every question.

1. What is your major investment objective?

a. High Return

b. Moderate return

c. Liquidity

d. Low risk

e. Safety

2. How would you allocate your funds?

Allocation of Funds (Options)

Stocks (%)

Mutual Funds (%)

Real Estate (%)

Debt up to (%)

Fixed Deposits (%)

a 100 0 0 00 0

b 70 10-20 10-20 05 2

c 50 15-25 10-20 10 5

d 30 20-25 10-20 20 10

e 10 20-30 10-20 25 20

3. What is your investment horizon?

a. 3 to 6 months

b. 6 months to 1 year

c. 1 years to 3 years

d. 3 years to 5 years

e. > 5 years

4. What are your expectations on return from investment?

a. 50 to 100 %

b. 40 to 50 %

c. 20 to 40 %

d. 10 to 20 %

e. 5 to 10 %

5. What type of investor do you consider yourself?

a. High risk taker

b. Opportunistic Risk taker

c. Moderate risk taker

d. Low risk taker

e. I don‟t like taking risk

Total Score for Q. 8 ____________

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Section D: Personal Information:

Name: _______________________________________________________________

City:____________________________________________________

1. Gender: Male Female

2. Age(in years): 18 to 25 26 to 35 36 to 45

46 to 55 56 to 65 66 and above

3. What is the highest level of education you have reached?

Primary Secondary Higher Secondary

Diploma Graduation Post graduation

4. Your monthly Income (Before tax): Upto Rs. 10,000 Rs. 10,001 to Rs. 15,000 Rs. 15,001 to Rs. 20,000 Rs. 20,001 to Rs. 25,000 Rs. 25,001 and above

5. Stage in family life cycle:

Young single Young married without children

Young married with children Middle-aged married with children

Middle age married without dependent children Older married

Older unmarried If other, please specify ___________________

6. Employment structure: Full Time Salaried Part Time Salaried Casual Self employed

Housewife Retired Unemployed Student

7. Workplace activity: Working in Finance related industry (Bank, Accountant, CFP, MF, Investment Co., Insurance Co. etc) Not working in Finance related industry (Other than shown above) Other

8. Would you please mind telling me your total number of years of works experience (in years)? Less than five 6 to 10 11 to 20 21 to 30 30 & more

9. Monthly expenditure to total monthly income?

1 %to 50 % 51% to 60% 61 % to 70% 71 % to 80 % 81% to 90% More than 90%

10. Monthly savings to total monthly income? 01 % to 50 % 51% to 60% 61 % to 70% 71 to 80 % 81% to 90% More than 90%

11. While investing your fund, usually how many times you shop around/visit the market?

Zero 1 to 3 4 to 6 More than six

12. How long have you invested your saving?

Less than1 year 1-5 years

6-10 years More than 10 years

--------------THANK YOU----------------

354

ANNEXURE II

પ્રિમ ઉત્તયદાતા, શબેુચ્છાઓ વશ,

પ્રલબાગ અ: િાથપ્રભક આપ્રથિક વાક્ષયતા

૧. વાભાન્મ જ્ઞાન: નીચે આેર વલકલ્ોભાાંથી કમો વલકલ્ વાચો છે. યોકાણ _________ કયી ળકે છે.

અ. વયકાય ફ. વ્મક્તત ક. વ્મક્તત કાંની/ેઢી ભાત્ર અ. અને ફ. ભાત્ર ફ.અને ક. ભાત્ર ક. અને અ.

ઉય દળાાલેર ફધા જ ઉય દળાાલેરભાાંથી એકણ નહશ

૨. નાણાકીમ મલૂ્મ: ધાયો કે આની ાવે કુર વભરકતો રૂ. ૨૦,૦૦૦ ની છે, જેભાાંથી આે નાણાકીમ યોકાણના વલકલ્ો ભાાં રૂ. ૧૦,૦૦૦ યોકાણ(તયર વભરકત) છે; અને ફીજી ફાજુ આની ઉય રૂ. ૫,૦૦૦ નુાં દેવુાં છે, તો આ આની ચોખ્ખી/ખયી વભરકતોનુાં નાણાકીમ

મલૂ્મ કઈ યીતે ગણળો?

તયર વભરકત -- કુર દેવુાં કુર વભરકત -- કુર દેવુાં કુર વભરકત + તયર વભરકત કુર વભરકત + તયર વભરકત -- કુર દેવુાં ફાદ કયીને ઉય દળાાલેરભાાંથી એકણ નહશ ખફય નથી

૩. પ્રનકાર કયલામોગ્મ આલક: ધાયો કે આની ભાવવક આલક રૂ. ૧૦,૦૦૦ છે, જેના ઉય તભે રૂ. ૧,૦૦૦ નો આલક લેયો બયલા ાત્ર

છે, તો આની વનકાર કયલામોગ્મ આલક નીચે આેર વલકલ્ભાાંથી કમા વલકલ્થી પયક ડળે?

વ્મક્તતગત આલક લેયો વ્મક્તતગત ફચત વ્મક્તતગત ઘયગથ્થા ખચાા ભાવવક આલક= વનકાર કયલામોગ્મ આલક ઉય દળાાલેરભાાંથી એકણ નહશ ખફય નથી

૪. ફચતની મૂભતૂ જાણકાયી: નીચે દળાાલેર ખાતાઓના વલકલ્ોભાાંથી કયુાં ખાત ુાં એક વાભાન્મ વ્મક્તત ખોરી ળતતી નથી?

ફચત ખાત ુાં ચાલ ુખાત ુાં ડીભેટ ખાત ુાં

હપતવ હડોઝીટ ખાત ુાં યીકયીંગ હડોઝીટ ખાત ુાં ખફય નથી

૫. ગણતયી (વાદ ું વ્માજ): ધાયો કે આની ાવે આજે રૂ. ૧૦૦ ફેંકના ફચત ખાતાભાાં છે, જેના ય આને લાવિક ૨% રેખે વ્માજ વાદા વ્માજની દ્ધવતથી ભે છે, તો ફયાફય આજથી ૫ લા છી આના ખાતાભાાં કેટરા રૂવમા શળે, જો તભે તેભાાં વદૃ્ધદ્ધ ાભલા રૂવમા મકૂી યાખો તો?

રૂ. ૧૦૨ કયતા લધાયે રૂ. ૧૦૨ કયતા ઓછા રૂ. ૧૦૨

ઉય દળાાલેરભાાંથી એકણ નહશ ખફય નથી

૬. ગણતયી (ચક્રવદૃ્ધિ વ્માજ): ધાયો કે આની ાવે રૂ. ૧૦૦ ફેંક ફચત ખાતાભાાં છે, જેના ય આને લાવિક ૨૦% ના દયે ચક્રવદૃ્ધદ્ધ વ્માજ

ભે છે, અને આ ૫ લા સધુી તે રૂવમા ઉાડતા નથી, તો ૫ લાના અંતે આના ખાતાભાાં કુર કેટરા રૂવમા શળે?

રૂ. ૨૦૦ કયતા લધાયે રૂ. ૨૦૦ કયતા ઓછા રૂ. ૨૦૦ ઉય દળાાલેરભાાંથી એકણ નહશ ખફય નથી

હુાં, શાા જયીલારા, "To study the level of finacical literacy level and its impact on investment decision: An in-depth

analysis of investors in Gujarat state” ય ી.એચ.ડી. કરુાં છાં.આનો હકભતી જલાફ અને અભબપ્રામ ભને ભાયો અભ્માવ ણૂા કયલાભાાં ઉમોગી નીલડળે. હુાં આની આબાયી યશીળ, જો આ આના જ્ઞાન અને જાણકાયીને અનવુયીને નીચે આેર પ્રશ્નોના ઉત્તય અને ભાહશતી પ્રત્મેનો વાચો અભબપ્રામ આળો. હુાં તભને ખાતયી આુાં છાં કે આના દ્વાયા પ્રાપ્ત થમેર ભાહશતીનો ઉમોગ ભાત્ર અભ્માવના શતે ુઅથે જ કયલાભાાં આલળે અને તેને ણૂાણે ખાનગી યાખલાભાાં આલળે.

355

૭. ફૂગાલો: કલ્ના કયો કે આના ફચત ખાતા ય વ્માજ નો લાવિક દય ૧% છે, અને લાવિક ફૂગાલાનો દય ૨% છે, તો એક લા છી આના ફચત ખાતાભાાં યશરે રૂવમાથી નીચે આેર વલકલ્ોભાાંથી આ કેટલુાં ખયીદી ળકળો?

આજ કયતા લધાયે આજના જેટલુાં જ આજ કયતા ઓછા ખફય નથી

૮. નાણાુંન ું વભમમલૂ્મ: કલ્ના કયો કે એક વભત્રને આજે રૂ. ૧૦૦૦૦ લાયવાભાાં ભે છે, અને એની ફશનેને રૂ. ૧૦,૦૦૦ આજથી ૩ લા સધુી ભે છે, તો ફને્નભાાંથી લાયવાને કાયણે લધ ુૈવાદાય કોણ શળે?

વભત્ર એની ફશને ફને્ન ફયાફય ૈવાદાય ખફય નથી

૯. ળેય ફજાયની કાભગીયી: નીચે આેર વલકલ્ભાાંથી કમો વલકલ્ ળેય ફજાયની મખુ્મ કાભગીયી દળાાલે છે? ળેય ફજાયળેયની કભાણીનુાં બાલી જાણલા ભદદરૂ થામ છે,

ળેય ફજાય ળેયની કીભતભાાં લધાયો કયે છે,

ળેય ફજાય એલા રોકોને બેગા કયલાનુાં કાભ કયે છે જે ળેય ખયીદલા અને લેચલા ભાગતા શોમ,


૧૦. લૈપ્રલદ્યકયણ: જમાયે યોકાણકાય ોતાના રૂવમા એક કયતા લધાયે જુદા જુદા યોકાણના વલકલ્ોભાાં યોકે છે, ત્માયે રૂવમા ગભુાલાનુાં જોખભ

____________ . લધે છે ઘટે છે એભ જ યશ ેછે ખફય નથી

૧૧. રયસ્ક-યીટનન ટે્રડ ઓપ: વાભાન્મ યીતે કોઈ એક કાંનીના ખયીદેર ળેય, ળેય મચુ્યરુ પાંડ કયતા સયુભિત લતય/યીટના આે છે.

વાચુાં છે ખોટુાં છે ખફય નથી

૧૨. જોખભ: યોકાણભાાં જોખભની શાજયી એટરે _________.

યોકાણકાય રૂવમા ગભુાલળે. એક કયતા લધાયે હયણાભ ળક્ય છે.

ઉય મજુફ દળાાલેર ફાંને ઉય દળાાલેરભાાંથી એકણ નહશ ખફય નથી

૧૩. ફે યોકાણના પ્રલકલ્ લચ્ચેનો રયસ્ક-યીટનન ટે્રડ ઓપ: વાભાન્મ યીતે ળેય ફોન્ડ કયતા લધાયે સયુભિત શોમ છે.


૧૪. યોકાણના વભમગાા અને યોકાણ પ્રભરકતના મલૂ્મભાું વદૃ્ધિ લચ્ચેનો વુંફધ: એક રાાંફો વભમગાો વલચાયતા (દાખરા તયીકે ૧૦ થી ૨૦ લા), નીચે આેર કઈ યોકાણ વભરકત વાભાન્મ વાંજોગોભાાં લધાયે લતય/યીટના આળે?

ફચત ખાત ુાં ફોન્ડ ળેય


૧૫.યોકાણનો વભમગાો અને યોકાણના મલૂ્મભાું અસ્સ્થયતા: વાભાન્મ વાંજોગોભાાં નીચે દળાાલેર કમા યોકાણનુાં મલૂ્મભાાં વભમાાંતયે લધાયે

અક્થથયતા જોલા ભે છે?

ફચત ખાત ુાં ફોન્ડ ળેય


૧૬. પ્રભરકત/યોકાણની પાલણી: વભરકત/યોકાણની પાલણી એટરે _____ . અ. વનણામ કે જેભાાં યોકાણકાય ોતાના રૂવમા જોખભયહશત અને જોખભી યોકાણના વલકલ્ોભાાં પાલે છે.

ફ. વનણામ કે જેભાાં યોકાણકાય ોતાના રૂવમા અરગ અરગ જુદા જુદા જોખભી યોકાણના વલકલ્ોભાાં પાલે છે.

ક. ધ્માનલૂાક કયેર યોકાણનુાં વલશ્રેણ

અ. અને ફ. ફ.અને ક. ક. અને અ.

ઉય દળાાલેર ફધા જ ઉય દળાાલેરભાાંથી એકણ નહશ ખફય નથી

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૧૭. વ્માજ અને યોકાણ/પ્રભરકતની કીભત લચ્ચેનો વફુંધ: જો અથાળાસ્ત્રભાાં વ્માજનો દય ઘટે તો, ફોન્ડની કીભતભાાં ______ થામ.

લધાયો ઘટાડો એભ જ યશ ે ખફય નથી

૧૮. ગ્રાશકના શક અને જલાફદાયી: જો એક વ્મક્તત ોતાની ાવે ોતાના ફેંક ખાતાનુાં એ.ટી.એભ. કાડા અને તેનો P.I.N.(ીન) નાંફય

ોતાના વાભાાં મકેુ છે, જો વા ચોયાઈ જામ/ખોલામ જામ, અને ફીજી કોઈ વ્મક્તત તેના ીન નાંફય અને એ.ટી.એભ. કાડા નો ઉમોગ

કયી તેના ખાતાભાાંથી રૂવમા ઊડ ેછે, તો આ વાંજોગોભાાં કોણ જલાફદાય યશળેે?

ભાત્ર ફેંક ભાત્ર કાડાધાયક ફેંક અને કાડાધાયક/ફેંક ખાતાનો ભાભરકફને્ન ખફય નથી

૧૯. પ્રનમભો ફનાલતી વુંસ્થાઓ નાણાકીમ ભાખાના બાગરૂ: નીચે આેર પ્રલકલ્ોભાુંથી કઈ વુંસ્થા ાવે કામદેવયની વત્તા નથી. વેફી ઈયડા આય.ફી.આઈ. એમ્પી

ઉય દળાાલેર ફધા જ ઉય દળાાલેરભાાંથી એકણ નહશ ખફય નથી

૨૦. Know your client (KYC):"તભાયા ગ્રાશકને જાણો", આ રેખખત ત્રકનો ઉમોગ ગ્રાશકના તાદ્રશ્તાને િસ્તાપ્રત કયલાભાું થામ

છે.


પ્રલબાગ ફ: - એડલાુંવ આપ્રથિક વાક્ષયતા

નીચે મજુફ યોકાણકાયો ભાટે યોકાણના વલકલ્ોના રિણો આેર છે, આની વભજણ અને જ્ઞાન પ્રભાણે આ ભશયેફાની કયીને નીચે આેર

લાક્યો ખયા છે કે ખોટા તે કશો.(નોંધ: દયેક લાક્ય ભાટે કોઈ ણ એક વલકલ્ વાંદ કયો.)

ક્રભ યોકાણના પ્રલકલ્ોના રક્ષણો શા ના ખફય નથી રપક્વ રડોઝીટ

૧. આ ફેંકભાાં એકવાથે મકૂલાભાાં આલતી યકભ છે, જેના ય ચોક્કવ વભમ ભાટે ચોક્કવ દયે વ્માજ

ભે છે.

૨. જુદી જુદી ફેંકો દ્વાયા હપતવ હડોઝીટ ય આલાભાાં આલતો વ્માજનો દય એકવયખો શોમ

છે.

૩. હપતવ હડોઝીટ ય આલાભાાં આલતી વ્માજની ગણતયી ચક્રીવદૃ્ધી વ્માજની દ્ધવતથી કયલાભાાં આલે છે.

નેળનર વેપ્રલિંગ વટીપીકેટ

૪. આ રાાંફા વભમગાા ભાટે કયલાભાાં આલતુાં જોખભયહશત યોકાણ છે. .

૫. નેળનર વેવલિંગ વટીપીકેટવ કાંનીઓ દ્વાયા ફશાય ાડલાભાાં આલે છે.

૬. નેળનર વેવલિંગ વટીપીકેટવ ય વ્માજનો દય તેની યૂી મદુત સધુી એક જ યશ ેછે અને

વ્માજની ગણતયી લાભાાં ફે લખત કયલાભાાં આલે છે.

બ્લરક િોલીડુંટ પુંડ (ી.ી. એપ.)

૭. ી.ી. એપ. ભાાં લાવિક યોકાણ કયલા ભાટે કોઈ ભશત્તભ કે રઘતુ્તભ યોકાણભમાાદા નથી

૮. ી.ી. એપ. ભાાં યોકાણને રાગતો કોઈ રોક-ઇન-ીયીઅડ નથી.

૯. ી.ી. એપ. ભાાં કયેર લાવિક યોકાણ ય કોઈ ણ પ્રકાયની યોકાણ ભમાાદા લગય કયલેયાની ચકૂલાની લખતે યાશત આલાભાાં આલે છે.

એમ્પ્રોમી િોલીડુંટ પુંડ (ઈ.ી.એપ.)

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Total Score: /20 = /30 =_____/50

૧૦. ઈ.ી.એપ. ભાત્ર ગાય દાયોને રાગ ુડ ેછે

૧૧. ગાય દાય ઈ.ી.એપ. ભાાં પયજીમાતણે કયલાભાાં આલતા પાા કયતા લધાયે યકભ નુાં યોકાણ કયી ળકે છે.

૧૨. ઈ.ી.એપ. ભાાં ભાભરક દ્વાયા કયલાભાાં આલતી પાાની ફધી જ યકભ ગાયદાયના ઈ.ી.એપ.

ખાતાભાાં જામ છે.

ઇસ્ક્લટી ળેય

૧૩. ઇક્તલટી ળેયએ કાંનીની ભાભરકી દળાાલે છે.

૧૪. ઇક્તલટી ળેય ધાયક ને ઇક્તલટી ળેવા ય ભતુાં લતય/ હયટાન અવનિંગ ય ળેય કયીકે

ઓખલાભાાં આલે છે.

૧૫. ઇક્તલટી ળેય ય ડીલીડાંડની ચકૂલણી ળેયની ફજાય હકિંભત ય કયલાભાાં આલે છે.

િેપયન્વ ળેય

૧૬. પે્રપયન્વ ળેયધાયકોને ઇક્તલટી ળેવા ધાયકો કયતા ડીલીડાંડની ચકૂલણી લખતે પ્રથભ વાંદગી આલાભાાં આલે છે.

૧૭. પે્રપયન્વ ળેયધાયકોને કાંનીના વલવર્જન અને લેચાણ પ્રહક્રમાની આલકની લશચેણી કયતી લખતે

ઇક્તલટી ળેયધાયકો કયતા અને કાંનીની પ્રથભ વાંદગી આલાભાાં આલતી નથી

મ ચ્ય ર પુંડ

૧૮. જમાયે યોકાણકાય મચુ્યરુ પાંડભાાં યોકાણ કયે છે, ત્માયે વાભે તેને યવુનટ્વ આલાભાાં આલે છે.

૧૯. મચુ્યરુ પાંડના યવુનટની હકિંભત નેટ એથવેટ લેલ્ય ુતયીકે ઓખામ છે.

૨૦. મચુ્યરુ પાંડ એણે ફાશેંધયી આેર યીટનાના /લતયના દયે ચકૂલણી કયે છે, જે તેના ભતૂકાની કાભગીયી ય આધાહયત શોમ છે.

ફોન્ડઅને ડીફેન્ચય

૨૧. ફોન્ડ અને ડીફેન્ચયભાાં કયલાભાાં આલતુાં યોકાણ આલકલેયા ભાાં ભલાાત્ર યાશત ભાટે મોગ્મ

નથી.

૨૨. ફોન્ડ અને ડીફેન્ચય ય ભતુાં લતય/ યીટના ાકતી મદુત સધુી એકવયખુાં જ યશ ેછે.

૨૩. જો કોઈ વ્મક્તત કોઈ કાંનીના ડીફેન્ચય ખયીદે છે, તો એ ખયીદેર ડીફેન્ચય હકિંભત જેટરી કાંનીની ભાભરકી બોગલે છે.

ોસ્ટ ઓપીવ ભાપ્રવક આલક મોજના

૨૪. ોથટ ઓપીવ ભાવવક આલક મોજનાભાાં કયેર યોકાણ ભાટે બાયત વયકાય કોઈ ણ પ્રકાયની ફાશેંધયી આતી નથી.

૨૫. ોથટ ઓપીવ ભાવવક આલક મોજનાભાાં કોઈ ણ પ્રકાયની ફાાંધી મદુ્દત શોતી નથી.

૨૬. ોથટ ઓપીવ ભાવવક આલક મોજનાભાાં તેની મદુ્દતવભમ દયમ્માન યોકાણ કામાના એક લા છી જો નાણાાંનો ઉાડ કયલાભાાં આલે તો તે દાંડ ને ાત્ર નથી.

જીલન લીભા ોરીવી

૨૭. લીભા ોરીવીભાાં ફધા જ પ્રકાયની ફીભાયીઓને સયુભિત કયલાભાાં આલે છે.

૨૮. એક વ્મક્તતના નાભની જીલન લીભા ોરીવી ફીજી વ્મક્તતના નાભ ય તફદીર કયી ળકામ છે.

૨૯. જીલન લીભાના પ્રીભીંમભની ચકૂલણી આલકલેયા ની કરભ ૮૦-C ભાાં યાશત ભલાાત્ર નથી.

૩૦. જીલન લીભાની ાતતની મદુતે લીભેદાયને ચકૂલલાભાાં આલતી યકભ કયાત્ર છે.

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પ્રલબાગ ક: નાણાકીમ યોકાણ પ્રનણનમ: િશ્નાલરી

૧. શુાં તભે તભાયી ફચતભાાંથી યોકાણ કયો છો?

શા (પ્રશ્ન ક્રભાાંક ફે ય જાઓ) ના (પ્રશ્ન ક્રભાાંક ચાય ય જાઓ)

૨. નીચે આેરા ફચત/યોકાણના વલકલ્ોભાાંથી આે કમા વલકલ્ોભાાં યોકાણ કયુું છે?

ોથટ ઓપીવ ફચત મોજના (NSC/KVP/PPF etc.) લીભા ોરીવી ફેંક હડોઝીટ (થાણ) મચુ્યરુ પાંડ

ળેય ફોન્્વ અને ડીફેન્ચયવ

હયઅર ઇથટેટ વોનુાં અને ચાાંદી

૩. જો આની ાવે રૂ. ‘X’ નુાં બાંડો/ફચત શોમ તો નીચે આેરા વલકલ્ોભાાંથી આ કમા વલકલ્ભાાં રૂવમા યોકલાનુાં વાંદ કયળો? (ચઢતા ક્રભભાાં ગોઠલો, જેભાાં ભશત્તભ વાંદગી ને એકથી ળરુ કયો.) ોથટ ઓપીવ ફચત મોજના (NSC/KVP/PPF etc.) લીભા ોરીવી ફેંક હડોઝીટ (થાણ) મચુ્યરુ પાંડ

ળેય ફોન્્વ અને ડીફેન્ચયવ

હયઅર ઇથટેટ વોનુાં અને ચાાંદી

૪. નીચેઆેરા કાયણો ભાાંથી કયુાં કાયણ આને યોકાણ કયતા યોકે/અટકાલે છે?

ભને ભાયા શાથભાાં યેુયુી તયરતા જોઈએ છે . ભને યોકાણ કયલાની જરૂય નથી

ભાયી ાવે યોકાણનુાં જ્ઞ્ઞાન નથી ભાયી ાવે યોકાણ ભાટે યૂતા રૂવમા નથી

હુાં યોકાણ કયલાભાાં ભાનતો નથી હુાં યોકાણ કયલા ભાટે યુતો વભમ પાલી ળકતો નથી. ભને યોકાણ કયલાથી કોઈ રાબ દેખાતો નથી હુાં કોઈ ણ એડલાઈવય/કમ્નીએ આેર ભાહશતી ય વલશ્વાવ યાખતો નથી યોકાણની પ્રવવૃત્ત ભને ગ ૂાંચલણીબયી રાગે છે ભને યોકાણ ના ફધા જ વલકલ્ો જોખભી રાગે છે

એડલાઈવય/કમ્નીની ઊંચી પીવને કાયણે હુાં યોકાણ કયલાનુાં ડતુાં મકુૂાં છ. (પ્રલબાગ ડ ય જાઓ)

૫. નીચે મજુફ યોકાણ કયલાના શતે ુદળાાલેર છે, કૃા કયી આ આનો યોકાણ ાછનો શતે ુજણાલો. (ચઢતા ક્રભભાાં ગોઠલો, જેભાાં ભશત્તભ

વાંદગી ને એકથી ળરુ કયો.) ઇન્કભ ટેિભાાં યાશત ભાટે ભાયા ફાકના રગ્ન/વાભાજજક પ્રવાંગો/વળિણ ભાટે નાણાકીમ જોગલાઈભાટે

ભકાન ખયીદલા/ યીનોલેળન કયલા ભાટે વનવવૃત્ત દયમ્માન નાણાકીમ વનવિતતા/સયુિા ભેલલા ભાટે

બેટ/ડોનેળન/ આલા ભાટે/ માત્રા કયલા ભાટે બવલષ્મભાાં થનાયા અજાણતા ખચાાઓને શોચી લલા ભાટે

લતાભાન નાણાકીમ બાંડોની વદૃ્ધદ્ધ કયલા ભાટે/ ફૂગાલા વાભે નાણાકીમ સયુિા ભેલલા

359

૬.આ યોકાણ કયતા શરેા નીચે આેર કમા વલકલ્ોભાાંથી યોકાણની ભાહશતી રેલાની વાંદ કયળો?.

ક્રભ પ્રલકલ્ો વુંદ

નરશ કયીએ

ઓછી વુંદ

કયીશ ું

તટસ્થ વુંદ

કયીશ ું વૌથી લધાયે વુંદ

કયીશ ું 1 વહટિપાઈડ પાઈનાક્ન્વઅર પ્રાનય

2 કાંની ના લાવિક અશલેારો યથી

3 કાંની ના પ્રોથેતટવભાાંથી

4 કાંનીની લેફવાઈટ યથી

5 પાઈનાક્ન્વઅર પ્રોડતટ્વના ડીથરીબ્યટુવા

6 યેહટિંગ એજન્વીઓએ આેરા યીોટાવભાાંથી

7 કાંની ના ટેભરપોન યીપે્રઝેન્ટેટીલ ાવેથી

8 કુટુાંફના વભ્મો ાવેથી

9 વભત્રો અને વફાંધીઓ ાવેથી

10 પ્રોપેળનર કરીગ્વ વાથેના ચચાા/ લાતાારા દ્વાયા

11 પાઈનાક્ન્વઅર પે્રવ/લતાભાનત્રોભાાં કે ઈરેતરોવનક ભીહડમાથી થમેર બ્રીકેળન દ્વાયા

12 કાંની એતવીક્યટુીલ અને વેતટય એિટા વાથેના ચચાા/લાતાારા દ્વાયા

13 થલતાંત્ર ઇન્લેથટભેન્ટ કમ્નીએ દળાાલેર કાંની ના બાવલ વલે

14 યીવચા એજન્વીઓએ બ્રીળ કયેરા યીોટાવ/અશલેારોભાાંથી

15 પ્રલતાભાન કે શારના યોકાણકાયો ાવેથી

16 પાઈનાક્ન્વઅર એડલાઈવય/બ્રોકય એ આેરા સચૂનો યથી

૭. આના યોકાણના વનણામને અવય કયતા નીચે મજુફ કેટરાક હયફો આેર છે, તેઓ આના યોકાણ ના વનણામને કમા પ્રભાણ થી અવય

કયે છે, તે જણાલો.

ક્રભ રયફો અવય કયતા નથી

આંપ્રળક

અવય તટસ્થ ભશત્લ

ની અવય

કયે છે

વૌથી લધાયે/ વૌથી ભશત્લની અવય કયે છે

1 નાણાકીમ અશલેારોની ક્થથવત

2 કાંની/ેઢીની અંદાજીત એકવત્રત આલક

3 કાંની/ેઢીની ભતૂકાની કાભગીયી( કાંનીએ કયેર નપો અને યોકાણકાયોને

આેર લતયની દ્રષ્ટીએ)

4 ઔદ્યોભગક શયણપાભાાં કાંની/ેઢીનુાં થથાન

5 કાંની/ેઢીની અંદયની વ્મક્તતએ આેર ભાહશતી

6 મૂભતૂ વલષ્રેણ(fundamental analysis)નુાં હયણાભ

7 તકનીકી વલષ્રેણ(Technical analysis)નુાં હયણાભ

8 આના યોકાણ ય આે ધયેર લતય

360

અવય કયતા નથી

આંપ્રળક

અવય તટસ્થ ભશત્લ

ની અવય

કયે છે

વૌથી લધાયે/ વૌથી ભશત્લની અવય કયે છે

9 કાંની/ેઢીની પ્રોડતટ્વ/ વવલિવીવ યામે આની રાગણી/બાલ

10 કાંની/ેઢીના નૈવતક મલૂ્મોની પ્રત્મેની કદયની સઝૂ/ખ્માર

11 કાંની/ેઢી વાથે યાજકીમ ભાંડ(political party)વાથે જોડાણ

12 વાભાજજક િેત્રભાાં પાો

13 લતાભાન ત્રોભાાં આલતા અશલેારો યથી

14 થટોક ભાકેટભાાં કાંનીના ળેયની શારની હકિંભતભાાં થતી લધઘટ / એન.એ.લી

15 વત્તાલાય/અવધકાયી કે યાજકીમ િના નેતાએ આેર અશલેાર/ત્રક

16 દુવનમાના ભોટા ળેય ફજાયોભાાં પ્રલતાતી અક્થથયતા/ વલકાવ

17 અથાળાસ્ત્ર ના પ્રલતાભાન વનદેળનો

18 આણા દેળભાાં કાંનીની ળાખ

19 કાંનીની ેયન્ટ કાંની કે વવથટય કાંનીની ળાખ

20 માાલયણ ને રગતા કાંની અશલેારોની માદી

21 કાંનીનુાં ભાકેટ કેીટરાઈઝેળન

22 પ્રોપેળનર કરીગ્વ વાથે થમેર ચચાા/ લાતાારા

23 પાઈનાક્ન્વઅર પે્રવ કે ઈરેતરોવનક ભીહડમાથી થમેર બ્રીકેળન

24 કાંની ઇતઝેકુતીલ અને વેતટય એક્ષ્તા વાથે થમેર ચચાા/લાતાારા

25 ફજાયભાાં યોકાણ કયતા અન્મ યોકાણકાયો ના ોટાપોરીઓનો અભ્માવ

26 થલતાંત્ર ઇન્લેથત્ભેન્ત કમ્નીએ દળાાલેર કાંનીના બાવલ વલે

27 યીવચા એજન્વીઓએ ફનાલેર અથાળાસ્ત્રના બાવલ વલેના અશલેારો

28 કાંની ના લાવિક અશલેારોનો અભ્માવ

29 કુટુાંફના વભ્મોનો ભત/ભાંતવ્મ

30 વભત્રો અને વફાંધીઓનો ભત/ભાંતવ્મ

31 પ્રલતાભાન કે શારના યોકાણકાયોનો ભત/ભાંતવ્મ

32 પાઈનાક્ન્વઅર એડલાઈવય/બ્રોકય એ આેરા સચૂનો

33 યેહટિંગ એજન્વીઓએ આેરા યીોટાવના ભત/ભાંતવ્મ

34 આે કયેર કુર યોકાણભાાં લૈવલદ્યતાની જરૂહયમાત (કુર યોકાણભાાં ડાઈલવીપીકેળનની જરૂહયમાત)

35 કુર યોકાણને રગતી તયરતાની જરૂહયમાત

36 આલક લેયા(ઇન્કભ ટેિ)ભાાં ભતી યાશત

37 હયથક-યીટના રેડ ઓપ

38 કુર યોકાણ ને રગતા બમ (હયથક) ને ઓછાં કયલાની જરૂયીમાત

39 ઊછીના રૂવમા રેલાની વયતાની વ્મલથથા

40 યોકાણ વાથે વાંકામેર વભમમદુત

41 યોકાણના વલકલ્ વાથે વાંકામેર મદુ્દરની સયુિા

42 યોકાણના વલકલ્ને શોચી લલા યોકાણ કયલા જોઈતી ઓછાભાાં ઓછી યકભ

361

૮. આ કમા પ્રકાયના યોકાણકાય છો, તે જાણલા નીચે મજુફ નાના પ્રશ્નો આેર છે, આેર વલકલ્ોભાાંથી એક વલકલ્ વાંદ કયો: (નોધ:

વાંદ કયેર વલકલ્ ભાટે કોઈ ગણુ નથી.)

૧. નીચે આેર વલકલ્ોભાાંથી આનો યોકાણ કયલા ભાટે ભશત્લનો ઉદે્દશ્મ કમો છે? High Return

અ. ઊંચુાં યીટના/લતય ફ. ભધ્મભ યીટના/લતય ક. તયરતા ડ. ઓછાં જોખભ ઈ. સયુિા

૨. નીચે આેર વલકલ્ોભાાંથી આ ોતાની ફચતનુાં કઈ યીતે યોકાણ કયલાનુાં વાંદ કયળો?

કુર યોકાણની પાલણી (વલકલ્ો)

ળેય (%) મચુ્યરુ પાં્વ

(%)

હયઅર ઇથટેટ

(%)

ફોન્્વ અને

ડીફેન્ચયવ

(%)

પીિ ડીોવવટ

(%)

અ. ૧૦૦ ૦ ૦ ૦ ૦

ફ. ૭૦ ૧૦-૨૦ ૧૦-૨૦ ૫ ૨

ક. ૫૦ ૧૫-૨૫ ૧૦-૨૦ ૧૦ ૫

ડ. ૩૦ ૨૦-૨૫ ૧૦-૨૦ ૨૦ ૧૦

ઈ. ૧૦ ૨૦-૩૦ ૧૦-૨૦ ૨૫ ૨૦

૩. નીચે આેર વલકલ્ોભાાંથી આની યોકાણ ભાટે ભાટેની વભમ મદુત ભાટેની વાંદગી કઈ છે?

અ ૩ થી ૬ ભહશના ફ. ૧ લા થી ૩ લા ક. ૩ લા થી ૫ લા ઈ. ૫ લાથી લધ ુ

૪. નીચે આેર વલકલ્ોભાાંથી આે કયેર યોકાણથી આને કેટલુાં લતય/યીટના ભળે એભ આ ધાયો છો?

અ. ૫૦-૧૦૦ %

ફ. ૪૦-૫૦ %

ક. ૨૦-૪૦ %

ડ. ૧૦-૨૦%

૫. નીચે આેર વલકલ્ોભાાંથી આ આને કમા પ્રકાયના યોકાણકાય ભાનો છો?

અ. ઊંચુાં જોખભ રેનાય

ફ. તક ભે તો જોખભ રેલાની તૈમાયી ફતાલનાય

ક. ભાધ્મભ પ્રકાયનુાં જોખભ રેનાય

ડ. ઓછાં જોખભ રેનાય

ઈ. ભને જોખભ રેવુાં ગભતુાં નથી Total Score for Q. 8 ____________

43 રૂવમાભાાં રૂાાંતય કયલાની વયતા

44 યોકાણ ય ભનાય ગેયેન્ટીડ હયટના/ લતય

362

પ્રલબાગ ડ: વ્મસ્ક્તગત ભારશતી નાભ: _______________________________________________________________ ળશયે:_____________________

૧. જાપ્રત: પ ર સ્ત્રી

૨. ઉભય (લોભાું): ૧૮ થી ૨૫ ૨૬ થી ૩૫ ૩૬ થી ૪૫

૪૬ થી ૫૫ ૫૬ થી ૬૫ ૬૬ અને તેથી ઉય

૩. આન ું ભશત્તભ પ્રળક્ષણ: પ્રાથવભક ભાધ્મવભક ઉચ્ચત્તય ભાધ્મવભક

ડીપ્રોભાાં થનાતક થનાતકોત્તય

૪. આની ભાપ્રવક આલક (કયાત્ર):

રૂ. ૧૦,૦૦૦ અનેતેથી ઓછી રૂ. ૧૦,૦૦૧ થી રૂ. ૧૫,૦૦૦ રૂ. ૧૫,૦૦૧ થી રૂ.૨૦,૦૦૦

રૂ. ૨૦,૦૦૧ થી રૂ. ૨૫,૦૦૦ રૂ. ૨૫,૦૦૧ અને તેથી લધ ુ

૫. ક ટ ુંફજીલન ચક્રનો તફક્કો: યલુાન એકર યલુાન યભણત વન:વાંતાન

યલુાન યભણત વાંતાન વાથે ભધ્મભ ઉંભય યભણત વાંતાન વાથે

ભધ્મભ ઉંભય યભણત યાંત ુવાંતાન અલરાંભફત ના શોમ વદૃ્ધ યભણત

વદૃ્ધ અયભણત અન્મ, _________________

૬. યોજગાયીન ું ભાખ ું: ણૂા વભમ ગાયદાય ઓછા વભમ ગાયદાય છૂટક થલયોજગાય ગહૃશણી વનવતૃ્ત વલદ્યાથી અન્મ ______________

૭. કામનકે્ષત્રની િવપૃ્રત્ત પાઈનાન્વ વાંફાંધી કામાિેત્રભાાં પ્રવવૃત્તભમ (ફેંક,એકાઉટાંટ,મચુ્યરુ પાં્વ,વવતિહપઈડ પાઈનાક્ન્વઅર પ્રાનય,ઇન્લેથત્ભેન્ત,ઇન્થયયુન્વ કાંનીભાાં ઇ.) પાઈનાન્વ અવાંફાંધી કામાિેત્રભાાં પ્રવવૃત્તભમ (ઉય દળાાલેર િેત્રો વવલામનુાં કામાિેત્ર)

અન્મ

૮. આનો ક ર કાભનો તજ ફો (લોભાું): ૫ કે તેના કયાંતા ઓછા ૬ થી ૧૦ ૧૧ થી ૨૦

૨૧ થી ૩૦ ૩૧ કે તેથી લધ ુ

૯. આના ભાપ્રવક ખચાન આની ભાપ્રવક આલકના િભાણભાું: ૧% થી ૫૦% ૫૧% થી ૬૦% ૬૧ % to ૭૦%

૭૧ % to ૮૦% ૮૧% to ૯૦% ૯૧% કે તેથી લધ ુ

૧૦. આની ભાપ્રવક ફચત આની ભાપ્રવક આલકના િભાણભાું: ૧% થી ૫૦% ૫૧% થી ૬૦% ૬૧ % to ૭૦%

૭૧ % to ૮૦% ૮૧% to ૯૦% ૯૧% કે તેથી લધ ુ

૧૧. યોકાણ કયતી લખતે ભારશતી ભેલલાના ઉદે્દશ્મથી આ વાભાન્મ યીતે કેટરી લાય પછૂયછ કયો છો/ કે એ જ ઉદે્દશ્મથી કેટરીલાય ફશાય જાઓ છો?

શનૂ્મ લખત ૧ થી ૩ ૪ થી ૬ ૭ કે તેથી લધ ુ

૧૨. આ અંદાજે કેટરા લોથી ોતાની ફચતભાુંથી યોકાણ કયો છો?

૧ લાથી ઓછાં ૧ થી ૫ લાથી

૬ થી ૧૦ લાથી ૧૧ કે તેથી લધ ુલોથી

------આબાય-----

List of Publications

371

1) Jariwala, H. (2010). Strategic approach to investment: A new paradigm in

financial planning. In I. E. S.Centre (Ed.), The Role of Financial Innovation:

Corporate Sustenance and Growth. Mumbai: Excel India Publishers.

2) Jariwala, H. & Sharma, S. (2011). Financial literacy: A call for an attention.

International Journal of Academic Conference Proceedings, 1(1), Washington

DC, USA: Library of Congress.

3) Jariwala, H. (2010). Developing Financial Literacy among Indian Masses. In

Amarnani, N. & Danak, D. (Eds.), Sustaining Shareholder Value: Corporate

Finance Practices. Ahmedabad: Excel India Publishers.

4) Jariwala, H., Sharma, M., & Patel, H. (2012). Young students’ towards financial

education. GFJMR, IV (January- June), pp. 15-37.

5) Jariwala, H., & Pandya,K. (2012). Investors’ behavior of equity investment: An

empirical study of individual investors. GFJMR, V (July- December), pp.1-32.

6) Jariwala, H. & Sharma, M. (2013). Assessment of behavioral outcomes of

financial education workshops on financial behavior of participants: An

experimental study. Journal of Financial Services Marketing (Special Issue on

Financial Literacy) 3. U.K.: Pal grave Macmillan.