Sources of Size Effect-Evidence From the Indian Stock Market-Santhosh Kumar S-0499

8/7/2019 Sources of Size Effect-Evidence From the Indian Stock Market-Santhosh Kumar S-0499

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Sources of Size Effect

M P Birla Institute of Management

A RESEARCH REPORT

ON

Sources of size effect-Evidence from the Indian stock market

Submitted in partial fulfillment of the requirements of

the M.B.A Degree Course of Bangalore University

Submitted By

SANTHOSH KUMAR.S

(REGD.NO:04XQCM 6078)Under the Guidance and SupervisionOf

PROF. B.V.RUDRA MURTHY

M.P.BIRLA INSTITUTE OF MANAGEMENT

Associate Bharatiya Vidya Bhavan

# 43, Race Course Road, Bangalore-560001

2004-2006


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Declaration

I hereby declare that this report titled Sources of size effect-Evidence from the

Indian stock market is a record of independent work carried out by me, towards the

partial fulfillment of requirements for MBA course of Bangalore University at M.P.Birla

Institute of Management. This has not been submitted in part or full towards any otherdegree.

PLACE: BANGALORE

DATE: SANTHOSH KUMAR.S


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Principals Certificate

This to certify that this report titled Sources of size effect-Evidence from the

Indian stock markethas been prepared by SANTHOSH KUMAR.S

bearing the registration no.04 XQCM 6078 under the guidance and supervision of

PROF. B.V.RUDRA MURTHY ,MPBIM, Bangalore.

Place: Bangalore Principal

Date: (Dr.N.S.Malavalli)


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GUIDES CERTIFICATE

This is to certify that the Research Report entitled Sources of size effect-Evidence

from the Indian stock market, done by SANTHOSH KUMAR.S bearing

Registration No.04 XQCM 6078 is a bonafide work done carried under my guidance

during the academic year 2005-06 in a partial fulfillment of the requirement for the

award of MBA degree by Bangalore University. To the best of my knowledge this

report has not formed the basis for the award of any other degree.

Place: Bangalore PROF.B.V.RUDRA MURTHYDate :


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ACKNOWLEDGEMENT

I am thankful to Dr.N.S.Malavalli, Principal, M.P.Birla institute of management,

Bangalore, who has given his valuable support during my project.

I am extremely thankful to PROF.B.V.RUDRA MURTHY, M.P.Birla institute of

Management, Bangalore, who has guided me to do this project by giving valuable

suggestions and advice.

I equally thank Dr T.V.N Rao for his guidance and suggestion.

Finally, I express my sincere gratitude to all my friends and well wishers who helped

me to do this project.

SANTHOSH KUMAR.S


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TABLE OF CONTENTS

CHAPTERS PARTICULARS

1. INTRODUCTION

CAPM model

Assumption of CAPM model

Misspecification of CAPM model

2. REVIEW OF LITERATURE

3. RESEARCH METHODOLOGY

Problem statement, objective of the study, scope of the study

Hypothesis, data, sample, sample size

Statistical procedures

4. DATA ANALYSIS AND INTREPRETATION

5. CONCLUSION

Glossary ,Bibliography


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INTRODUCTION:

Size effect implies that small firm stocks tend to outperform large firm stocks over a long

period of time. it has been found to be universal phenomenon. Studies have also shown thepresence of strong size effect in the Indian stock market.

There are different explanations of the documented size effect. One view point is that small

firms are inherently riskier than large firms owing to differences in their operating, financial

and liquidity risk characteristics .It has been empirically shown that small firms stocks are less

liquid and more neglected by institutional investors and security analysts. the studies have

shown that Small firms are exposed to higher operating and financial risks .They have lost

market values because of poor performance .they are inefficient producers, and are likely to

have high financial leverage and cash flow problems. Small firms tend to have poor customer

base, outdated technology, less diversified product lines and relatively lower access to financial

market.

The prices of the small firms stocks tend to be more sensitive to changes in the economy as

they are less likely to survive adverse economic conditions .however if the small firms are run

efficiently they may do well and even prosper in a economy which is growing slowly .but less

efficient firm may not survive at low growth rate in the long run.

If size as anomaly to the standard CAPM might have arisen due to the reason that beta is not

capturing the full systematic risk of small firms this implies beta is not a comprehensive risk

measure. If we believe that CAPM is a rational benchmark .then size effect is owing to

irrational investor behavior.


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CAPM

Capital asset pricing model referred to as CAPM, is a centerpiece of modern financial

economics. The model gives us a precise prediction of the relationship that we should observe

between the risk of an asset and its expected return.

ASSUMPTIONS OF CAPM MODEL:

1. Investors are risk averse individuals who maximize the expected utility of their end of

period wealth. Implication: The model is a one period model.

2. Investors have homogenous expectations about asset returns. Implication: all investors

perceive identical opportunity sets. This is, everyone have the same information at the

same time.

3. Asset returns are distributed by the normal distribution.

4. There exists a risk free asset and investors may borrow or lend unlimited amounts of

this asset at a constant rate: the risk free rate.

5. There are a definite number of assets and their quantities are fixed within the one period

world.

6. All assets are perfectly divisible and priced in a perfectly competitive marked.

Implication: e.g. human capital is non-existing (it is not divisible and it cant be owned

as an asset).

7. Asset markets are frictionless and information is costless and simultaneously available

to all investors. Implication: the borrowing rate equals the lending rate.

8. There are no market imperfections such as taxes, regulations, or restrictions on short

selling.


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According to CAPM

1. The risk of the project is measured by beta of the cash flow with respect to the

return on the market portfolio of all assets in the economy.

2. The relation between the required expected return and the beta are linear

According to CAPM equation,

E (Ri) = Rf+ [E (RM)-Rf] IM

Where, RF is the risk free rate of return.

Rm is the market return.

E (Ri) expected rate of return.

IMsystematic risk of market.

E (Rm)-RF is the risk premium.

Beta as a Measure of Systematic Risk:

An asset exhibits both systematic and unsystematic risk. The portion of its volatility which is

considered systematic is measured by the degree to which its returns vary relative to those of

the overall market. To quantify this relative volatility, a parameter called beta was conceived as

a measure of the risk contribution of an individual security to a well diversified portfolio:

IM=Cov (RA,Rm)/m

2

Where, RA is the return of the asset.

Rm is the return of the market.

IM is the variance of the return of the market, and

Cov(RA,Rm) is covariance between the return of the market and the return of the asset.

In simple words beta is the ratio of the expected excess return of an asset relative to the overall

markets excess return, where excess return is defined as the return on any given asset less the

return on a risk-free asset.


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CAPM decomposes a portfolio's risk into systematic and specific risk. Systematic risk is the

risk of holding the market portfolio. As the market moves, each individual asset is more or less

affected. To the extent that any asset participates in such general market moves, that asset

entails systematic risk. Specific risk is the risk which is unique to an individual asset. It

represents the component of an asset's return which is uncorrelated with general market moves.

According to CAPM, the marketplace compensates investors for taking systematic risk but not

for taking specific risk. This is because specific risk can be diversified away. When an investor

holds the market portfolio, each individual asset in that portfolio entails specific risk, but

through diversification, the investor's net exposure is just the systematic risk of the market

portfolio.

Formula is the essential conclusion of CAPM. It states that a stocks (or portfolio's) excess

expected return depends on its beta and not its volatility. Stated another way, excess return

depends upon systematic risk and not on total risk.

We call CAPM a "capital asset pricing model" because, given a beta and an expected return for

an asset, investors will bid its current price up or down, and adjusting that expected return so

that it satisfies formula.

Accordingly, the CAPM predicts the equilibrium price of an asset. This works because the

model assumes that all investors agree on the beta and expected return of any asset. In practice,

this assumption is unreasonable, so the CAPM is largely of theoretical value.

The CAPM and Liquidity:

Liquidity refers to the ease with which an asset can be converted into cash that is sold someevidence suggests that illiquidity can reduce market prices substantially.

A rigorous treatment of the value of the liquidity was first developed by Amihud and

Mendelson .liquidity plays an important role in explaining rates of return on financial assets

.investors prefer more liquid assets with lower transaction costs .relatively illiquid assets trade

at lower prices or equivalently expected return on illiquid assets must be higher .


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Misspecification of CAPM Model

CAPM is probably the most well known and utilized model of asset valuation, but do exist

several problems with it.

1. The CAPM is derived only under several very strict and unrealistic assumptions

2. The CAPM was originally derived as a static model of asset valuation. Hence,

the model did not account for the dynamic nature of financial markets with

respect to determination of rates of return.

3. The CAPM was originally developed to theoretically be a link between the

financial and real sectors of the economy.


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Rolf W Banz: Relationship between Return and Market value of Common

stocks: March 1981, Journal of financial economics volume 9.

This paper examines the empirical relationship between the return and the market value of the

NYSE common stocks .It is found that smaller firms have had higher risk adjusted returns onaverage than large firms and evidence that CAPM is mis specified.

Summary of the paper:

Single period CAPM postulates a simple linear relationship between expected return and the

market risk of a security .But results are inconclusive.

Evidence suggests that additional factors are relevant for asset pricing, litzenberger &

Ramaswamy (1979), Basu (1977).results of the study are not based on a particular equilibrium

model. so it is not possible to determine whether market value matters or whatever it is only

proxy for unknown true additional factors correlated with market value.

Data:

Sample includes all common stocks quoted on the NYSE between 1926 and 1975, monthly

price and return data & no of shares outstanding at the end of each month. Three different

market indices are used CRSP-equally and value weighted indices, combination of value

weighted index & return data on corporate & government bonds.

Methodology:

Then they selected 25 portfolios first one to five on the basis of market value. Then securities

in each of those five are in assigned to one of five portfolios on the basis of their beta. Next

five years data are used for the re estimation of the security beta .stock prices and number of

shares outstanding at the end of five year periods is used for the calculation of the market

proportion. the cross-sectional regression is performed in each month.


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Conclusions:

Evidence presented in this paper suggests that the CAPM is mis specified .small NYSE firms

have had significantly larger risk adjusted returns than large NYSE firms over a forty year

period. The size effect exists but it is not at all clear why it exists .so it should be interpreted

with caution. it might be tempting to use the size effect e g: as the basis for the theory of

mergers larger firms are able to pay a premium for the smaller stocks since they will be able to

discount the same cash flows at a smaller discount rate .naturally, this might turn out to be

complete nonsense if size were to be shown to be just a proxy.

Christopher James and Robert o Edmister:-The Relationship between

Common Stock Returns, Trading Activity and Market Value September 1983,

Journal of finance volume 38

This study examines the relation between common stock returns, trading activity and market

value .results indicate that although firm size and trading activity are highly correlated,

differences in trading activity are not the underlying reason for the firm size anomaly the

finding of systematic differences in risk adjusted returns across stocks of firms different size.


Empirical research has revealed systematic differences in risk adjusted returns for the common

stocks of firms of different sizes as measured by the market value of outstanding common

stock BANZ (1981) , REINGANUM because of the small firm trade less frequently than large

firms ,risk measures obtained from daily or weekly returns data may seriously underestimate

the risk associated with holding a portfolio of small firms. Trading activity and firm size are

highly correlated however, no significant difference in mean daily risk adjusted returns is

observed between portfolios of the most actively traded firms and portfolios of the least

actively traded firms.


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Data and Sample Selection:

Common stock returns and trading volume information for the NYSE and AMEX firms

examined in this study and data were obtained from the DATA RESOURCES

INCORPORATED FILE. Then 500 issues were selected for period 1975-1979 then stratified

random sample was employed .to ensure that an equal number of firms from each size decile

was included in the sample for each sample two measures of trading activity were

calculated(1) average daily trading volume ,(2) number of trading days.

Methodology

For each of the 4 sample years 3 sets of 10 equally weighted portfolios were constructed, on

the basis of market value, average daily trading volume, number of days the firm traded

during the year. Then mean return was calculated by combining portfolio return series for each

of the four years and then taking the arithmetic mean .then risk adjusted returns were

calculated by subtracting from the daily return series the OLS estimate of beta times the return

in market portfolio

Then F test was used whether the mean returns of the smallest firm size portfolios are equal to

the mean returns on largest size portfolios.

Conclusion

Paper addresses the question of whether the firm size effect is explicable in terms of

differences in trading activity between the large and small firms because of either a liquidity

premium associated with small firms or a mis assessment of the risk of small firms. no

evidence is found consistent with existence of a liquidity premium moreover ,differences in

trading activity do not appear to fully explain the existence of firm size effect through bias in

the estimation of beta.


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An Exploratory Investigation of the Firm Size Effect 1985, Journal of financial

economics, volume 14.

This paper investigates the firm size effect in the frame work of multi factor pricing model.

The risk adjusted return between the top five percent and bottom five percent of the NYSEfirms.


Empirical study of arbitrage pricing model (APT) CHAN (1981) (1983) found that firm size

effect is essentially captured by the factor loading of APT.

To interpret the size effect K C CHAN used the identifiable economic variables directly in a

pricing equation. It is comparable with inter temporal pricing models such as those of

MERTON (1973), LONG (1974) , COX,INGERSOLL & ROLL (1976) here pricing equation

is called as multi factor pricing equation.

Stock market & macro economy:

Stock market reacts to changes in economic environment.

Here they used variables like

1. equity weighted NYSE index

2. value weighted NYSE index

3. monthly growth rates of industrial production( IPISA )

4. inflation

5. interest rates (T-bill)

6. A measure of change in the slope of the yield curve

Cross Sectional Results

DataInvestigation limits to the time period 1953-1977 and divided these 25 years into 20

overlapping intervals, like 1953 to 1958, 1954 to 1959 so on

.


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Methodology

After ranking the portfolios according to the firm size CHAN used FAMA & MACBETH

(1973) method to test the firm size effect. Then they performed the cross sectional regression

of the 20 portfolios. Then 2 two types of tests are performed with the residuals.

1. Univariate analysis

2. Paired T test

To see if the estimated residuals from the two extreme firm size portfolios are statically

different.

Conclusions

They first explored the feasibility of a multi factor pricing equation as an explanation of the

firm size effect evidence suggests that firm size anomaly is essentially captured by a multi

factor pricing model .the higher average returns of smaller firms are justified by the additional

risks borne in an efficient market.

Vijay B, AV vedpuriswar:-Small Firm Effect in the Indian Stock Market an

Empirical Study July 2002, journal of applied finance, volume 8

Small firm effect is a phenomenon where small firms have higher returns on average than large

firms. Such an anomaly would affect the pricing of capital assets.

Summary of the paper

Kiem (1983) has shown half of the small firms affect in January. The reasoning given by kiem

was that the investors sell securities at the end of the year to establish short term tax losses for

tax purposes this is seasonality in the stock returns, because in the new year stocks go back to

the equilibrium results creating the larger returns. Fama and French (1995) extended their work

to find relationship between firm size and firm earnings. They found that small firm effect is

prevalent and small firms have stronger earnings than larger firms. Sehgal and Kumar (2002)done study on Indian stock market and they found that small firms have abnormal returns and

more of small firms are having higher relative distress.


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Data

Study limits data of BSE 500 stocks and stocks are short listed to 273 on the basis of

continuously trading criteria from January 1991 to January 2002.

Methodology

In order to measure the returns monthly returns are used in the study then

Two value weighted portfolios are constructed on the basis of market value one portfolio

including 25 small stocks and other including 25 large stocks out of BSE 500 stocks.

Results

Results shows that the beta of the large firms are more or less equal to the market beta and

priced efficiently while smaller firms beta was less than one . it may be due to poor trading of

the small stocks whereby they are perceived to be less sensitive to the market movement. then

Jensens alpha is shows that on an average consistently outperform the market returns but

larger firms generate equal or less returns than market returns.

Conclusion

the descriptive statistics suggests that an average the mean, standard deviation, skewness of

small companies are higher than large firms and the result do not support the infrequent trading

is the main reason behind the small firm effect and differential growth rates between small

firms and large firms ,market index helps to unwind the small firm effect.


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PROBLEM STATEMENT:

The causes of the size effect in the Indian stock market

OBJECTIVE:To find whether size affects the operating, financial and liquidity charectestics of the firms

SCOPE OF THE STUDY:

The findings have implications on mutual fund managers and other investment strategists since

a major part of the size premium that they perceive as an opportunity for arbitrage could

actually be compensation for unaccounted risk.

HYPOTHESIS:

Null Hypothesis H0=the operating, financial and liquidity characteristics does not substantially

differentiates small firms from the larger ones

Alternative Hypothesis H1= the operating, financial and liquidity characteristics substantially

differentiates small firms from the larger ones

DATA:

Secondary data

The study uses the following accounting, financial and market related information regarding

the sample companies i.e. number of shares outstanding ,daily trading volume, share holding

patterns, book value per share ,market price per share ,total long term debt, equity capital,

operating profits(EBIT) ,net sales, fixed interest charges, capital employed ,total assets ,current

assets and current liabilities.


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Sources of data

All the necessary data for the study have been collected from PROWESS data base and

websites

Period of study

The study is conducted for a period of years starting from 2000 to 2004. Five years is taken, so

that the results presented are more accurate, where we can rely upon the results that are

calculated for the purpose of analysis. Also the analysis and conclusions will be more

accurate.

Sample

The sample for the purpose of the study consists of 60 companies forming part of CNX NIFTY

and CNX NIFTY JUNIOR over the period of 2000-2004.the sample has been selected because

a strong size effect has been found to exist on NSE using the same sample over the given

period.


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The following companies are included in the sample

CNX NIFTY NIFTY JUNIOR

Company Name Company Name

Bajaj Auto Ltd. Ashok Leyland Ltd.

Bharat Heavy Electricals Ltd. Asian Paints Ltd.

Bharat Petroleum Corpn. Ltd. Aurobindo Pharma Ltd.

Cipla Ltd. Aventis Pharma Ltd.

Dr. Reddy'S Laboratories Ltd. Bank Of Baroda

G A I L (India) Ltd. Bank Of India

H C L Technologies Ltd. Bharat Electronics Ltd.

H D F C Bank Ltd. Bharat Forge Ltd.

Hero Honda Motors Ltd. Cadila Healthcare Ltd.

Hindalco Industries Ltd. Container Corpn. Of India Ltd.Hindustan Lever Ltd. Corporation Bank

Hindustan Petroleum Corpn. Ltd. Cummins India Ltd.

Housing Development Finance Corpn Ltd. Great Eastern Shipping Co. Ltd.

I C I C I Bank Ltd. Industrial Development Bank Of India Ltd.

I T C Ltd. Ingersoll-Rand (India) Ltd.

Infosys Technologies Ltd. Kochi Refineries Ltd.

Larsen & Toubro Ltd. Moser Baer India Ltd.

Mahanagar Telephone Nigam Ltd. Mphasis B F L Ltd.

National Aluminium Co. Ltd. Nicholas Piramal India Ltd.

Oil & Natural Gas Corpn. Ltd. Nirma Ltd.

Ranbaxy Laboratories Ltd. Pfizer Ltd.

Reliance Energy Ltd. Polaris Software Lab Ltd.

Reliance Industries Ltd. Punjab Tractors Ltd.

Satyam Computer Services Ltd. Raymond Ltd.

State Bank Of India Reliance Capital Ltd.

Tata Motors Ltd. Siemens Ltd.

Tata Steel Ltd. Sterlite Industries (India) Ltd.

Videsh Sanchar Nigam Ltd. T V S Motor Co. Ltd.

Wipro Ltd. Tata Teleservices (Maharashtra) Ltd.

Zee Telefilms Ltd. Wockhardt Ltd.


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METHODOLOGY:

In December 2000 all the sample companies are ranked on the basis of market capitalization

for both CNX NIFTY and NIFTY JUNIOR indices .and two equally weighted portfolios

namely large firms portfolio consisting of top 30 stocks from CNX NIFTY with largest

market capitalization and small firms portfolio consisting of top 30 stocks from NIFTY

JUNIOR with largest market capitalization. then various operating, financial and liquidity

characteristics of the firms comprising these portfolios have been measured as at the end of the

December 2000.then same securities consisting portfolios are constructed every year at the end

of December till one reaches 2004.then averages of all the measures for the 5 years taken into

account to derive the different charectestics of small and large portfolio stocks.

STATISTICAL PROCEDURE:

Initially ANOVA a parametric test has been used to test for the significant differences among

means of various measures of small firms and large firms stocks.

ANOVA-Enables us to test for the significance among more than two sample means. We will

be able to make inferences about whether our samples are drawn from populations having the

same mean or not.

BASIC CONCEPTS:

Analysis of variance is based on a comparison of two different estimates of the variance, 2, of

our overall population; the three steps in analysis of variance are as follows

1. Determine one estimate of the population variance from the variance among the

sample means.

2. Determine second estimate of the population variance from the variance within

the sample means.

3. Compare these two estimates, if they are approximately equal in value, acceptthe null hypothesis. And if the they are not in equal in value then accept the

alternative hypothesis.


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Interpreting F RATIO

F statistic

F=between-column variance/within-column variance

The denominator and numerator should be about equal if the null hypothesis is true .the nearer

the F ratio comes to 1, then the more we inclined to accept the null hypothesis. Conversely, as

the F ratio becomes larger we will be more inclined to reject the null hypothesis and accept the

alternative hypothesis.

KRUSKAL- WALLIS TEST

Kruskal-Wallis tests a non parametric test extension of the Mann Whitney test to situations

where more than two populations are involved. This test depends on the ranks of the sample

observations.

The sampling distribution of the K statistic can be approximated by a chi-square distribution

when all the sample distributions are at least five. we can interpret that if the calculated value

is less than table value then null hypothesis is accepted and conclude that there are no

difference in the means of the samples. if the calculated value is greater than table value then

alternative hypothesis is accepted and conclude that there are difference in the means of the

samples.


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Exhibit-1


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Tables showing firms charectestics of S&P CNX NIFTY and S&P CNX NIFTY JUNIOR

companies.

S & P CNX NIFTYTABLE-1

Firms characteristics

Institutional

Investors Share

Company Name AVERAGE AVERAGE AVERAGE

Bajaj Auto Ltd. 23.2175 19.138 0.648

Bharat Heavy Electricals Ltd. 29.675 11.654 0.644

Bharat Petroleum Corpn. Ltd. 29.0275 4.494 2.726

Cipla Ltd. 25.8575 22.802 0.874

Dr. Reddy'S Laboratories Ltd. 32.705 23.818 0.742

G A I L (India) Ltd. 15.895 20.2 0.78

H C L Technologies Ltd. 12.415 49.518 0.342H D F C Bank Ltd. 32.885 70.978 0.08

Hero Honda Motors Ltd. 30.765 15.982 2.486

Hindalco Industries Ltd. 39.8025 35.996 0.402

Hindustan Lever Ltd. 26.555 19.522 1.472

Hindustan Petroleum Corpn. Ltd. 39.88 4.636 2.736

Housing Development Finance

Corpn Ltd. 63.8425 94.818 0.112

I C I C I Bank Ltd. 53.8925 77.14 0.076

I T C Ltd. 48.6225 38.95 0.682

Infosys Technologies Ltd. 47.3875 35.248 0.99Larsen & Toubro Ltd. 49.69 11.8 0.72

Mahanagar Telephone Nigam

Ltd. 33.78 27.898 0.322

National Aluminium Co. Ltd. 8.1475 35.812 0.452

Oil & Natural Gas Corpn. Ltd. 4.4225 53.57 0.384

Ranbaxy Laboratories Ltd. 36.34 17.012 1

Reliance Energy Ltd. 38.1275 14.048 0.54

Reliance Industries Ltd. 30.7825 13.918 0.86

Satyam Computer Services Ltd. 59.5175 29.762 0.878

State Bank Of India 71.8125 69.81 0.096Tata Motors Ltd. 35.1875 6.802 0.958

Tata Steel Ltd. 36.2125 15.682 0.65

Videsh Sanchar Nigam Ltd. 18.1775 32.794 0.698

Wipro Ltd. 4.4475 22.468 1.194

Zee Telefilms Ltd. 37.7575 53.896 0.106


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TABLE-2


Interest

coverage


Bajaj Auto Ltd. 18.978 0.22 278.83



Cipla Ltd. 31.56 0.072 65.582


G A I L (India) Ltd. 25.756 0.41 11.504

H C L Technologies Ltd. 18.662 0.008 113.058

H D F C Bank Ltd. 49.134 1.356 1.484Hero Honda Motors Ltd. 78.288 0.142 23.928




Housing Development Finance Corpn.Ltd. 11.722 7.146 1.4

I C I C I Bank Ltd. 28.418 4.27 1.174

I T C Ltd. 42.09 0.12 31.138

Infosys Technologies Ltd. 44.936 0 504.222

Larsen & Toubro Ltd. 17.292 0.924 2.162

Mahanagar Telephone Nigam Ltd. 15.55 0.214 29.55



Ranbaxy Laboratories Ltd. 27.894 0.066 25.1




State Bank Of India 79.846 0.946 1.192Tata Motors Ltd. 14.976 0.828 2.146

Tata Steel Ltd. 18.122 1.108 4.526


Wipro Ltd. 36.356 0.034 214.124



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TABLE-3

Firms characteristics Current ratio

BVPerShare/Adjusted

Closing Price


Bajaj Auto Ltd. 1.75 30.49 0.704



Cipla Ltd. 2.016 22.662 1.516


G A I L (India) Ltd. 1.31 35.496 0.832


H D F C Bank Ltd. 1.63 25.258 0.25





Housing Development Finance Corpn. Ltd. 1.414 47.586 0.426

I C I C I Bank Ltd. 3.31 31.106 0.568

I T C Ltd. 1.248 29.786 3.572

Infosys Technologies Ltd. 3.078 27.672 0.23









State Bank Of India 1.72 16 1.08

Tata Motors Ltd. 0.894 39.388 0.762

Tata Steel Ltd. 1.1 41.93 1.29


Wipro Ltd. 2.688 19.14 0.342



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TABLE-4


EPS

Adjusted Closing Price

Cash EPS


365 days

Avg. Traded

Quantity


Bajaj Auto Ltd. 0.11 0.146 126772.556



Cipla Ltd. 0.36 0.396 137802.144


G A I L (India) Ltd. 0.17 0.252 1220697.534


H D F C Bank Ltd. 0.042 0.042 182238.64





Housing Development Finance Corpn. td. 0.088 0.094 174829.662

I C I C I Bank Ltd. 0.078 0.078 696329.182

I T C Ltd. 0.91 1.054 492745.624

Infosys Technologies Ltd. 0.084 0.098 669236.396









State Bank Of India 0.172 0.172 2226206.43

Tata Motors Ltd. -0.02 0.06 2372532.96Tata Steel Ltd. 0.15 0.276 3907144.816


Wipro Ltd. 0.096 0.112 669912.284



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S&P CNX NIFTY JUNIORTABLE-5

Firms characteristicsInstitutional

Investors Share


Ashok Leyland Ltd. 32.3975 13.682 1.018

Asian Paints Ltd. 34.1725 16.34 1.648

Aurobindo Pharma Ltd. 23.3725 17.12 1.146

Aventis Pharma Ltd. 27.1475 21.134 1.302

Bank Of Baroda 19.2025 71.636 0.096

Bank Of India 8.245 68.774 0.094

Bharat Electronics Ltd. 14.035 19.048 0.712

Bharat Forge Ltd. 25.89 28.552 0.636

Cadila Healthcare Ltd. 13.2875 20.358 0.67

Container Corpn. Of India Ltd. 33.135 33.37 1.02

Corporation Bank 38.2075 79.674 0.1

Cummins India Ltd. 28.06 19.454 1.04

Great Eastern Shipping Co. Ltd. 23.8375 48.512 0.414

Industrial Development Bank Of India Ltd. 21.7975 89.858 0.116

Ingersoll-Rand (India) Ltd. 7.305 18.702 1.072

Kochi Refineries Ltd. 22.375 7.098 1.908

Moser Baer India Ltd. 20.725 45.98 0.354

Mphasis B F L Ltd. 23.77 29.894 0.538

Nicholas Piramal India Ltd. 15.7225 21.606 0.906

NirmaS Ltd. 0.79 25.08 0.726

Pfizer Ltd. 30.425 19.64 1.212

Polaris Software Lab Ltd. 23.31 25.31 0.956

Punjab Tractors Ltd. 58.22 17.722 1.22

Raymond Ltd. 33.6775 26.79 0.626

Reliance Capital Ltd. 5.775 98.008 0.126Siemens Ltd. 22.27 13.614 1.07

Sterlite Industries (India) Ltd. 10.4075 13.728 0.79

T V S Motor Co. Ltd. 18.2475 10.048 2.202

Tata Teleservices (Maharashtra) Ltd. 21.08 -29.222 0.126

Wockhardt Ltd. 10.8325 24.164 0.916


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TABLE-6


Interest

coverage



Asian Paints Ltd. 38.116 0.346 13.906



Bank Of Baroda 87.234 0.538 1.23

Bank Of India 68.834 1.654 1.178


Bharat Forge Ltd. 25.41 2.442 3.204










Mphasis B F L Ltd. 9.738 0.002 49.81


Nirma Ltd. 16.976 0.856 5.856

Pfizer Ltd. 38.158 0 162.928

Polaris Software Lab Ltd. 24.374 0 493.38


Raymond Ltd. 19.928 0.636 3.122

Reliance Capital Ltd. 10.886 1.48 1.36

Siemens Ltd. 35.914 0.04 18.218


T V S Motor Co. Ltd. 28.946 0.486 11.21

Tata Teleservices (Maharashtra) Ltd. -11.722 0.834 -1.164

Wockhardt Ltd. 26.808 0.43 11.672


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TABLE-7


Current

ratio



Asian Paints Ltd. 1.246 52.602 0.296



Bank Of Baroda 3.984 28.7 1.854

Bank Of India 3.716 30.434 1.894


Bharat Forge Ltd. 1.006 46.828 1.904









Moser Baer India Ltd. 2.162 8 1.24

Mphasis B F L Ltd. 2.954 6.694 6.912


Nirma Ltd. 2.462 12.846 0.55

Pfizer Ltd. 2.056 51.33 0.192



Raymond Ltd. 1.652 28.038 1.012


Siemens Ltd. 1.016 23.444 0.29


T V S Motor Co. Ltd. 1.08 29.57 5.014

Tata Teleservices (Maharashtra) Ltd. 0.254 0 0.538

Wockhardt Ltd. 2.106 28.666 0.672


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TABLE-8


EPS


Cash EPS


365 days

Avg. Traded

Quantity



Asian Paints Ltd. 0.076 0.098 20589.288



Bank Of Baroda 0.246 0.246 858256.806

Bank Of India 0.288 0.288 936685.108


Bharat Forge Ltd. 0.314 0.608 36072.354










Mphasis B F L Ltd. 0.232 0.314 34870.34


Nirma Ltd. 0.08 0.134 17555.75

Pfizer Ltd. 0.042 0.046 17041.368



Raymond Ltd. 0.182 0.256 189736.076


Siemens Ltd. 0.072 0.098 29393.21


T V S Motor Co. Ltd. 0.914 1.556 65551.176

Tata Teleservices (Maharashtra) Ltd. -0.12 -0.042 1515368.272

Wockhardt Ltd. 0.14 0.158 32265.638


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RESULTS:

ANOVA

Institutional Investors share TABLE-9

Sum of Squares df Mean Square F

Between Groups 2031.267 1 2031.267 10.059

Within Groups 11712.474 58 201.939

Total 13743.742 59

Interpretation:

Among the various measures tested, for institutional investor share we have got the F value as

10.059. As the F value is greater than 3 it is significant at 5% level. Therefore we reject the

null hypothesis and accept the alternative hypothesis, which states that there is significant

difference in the means of institutional ownership holdings of small and large size firms and

also we found that stocks of small firms are more neglected by institutional investors than

those of large firms.

Operating Ratio TABLE-10


Between Groups 19.828 1 19.828 0.032

Within Groups 36401.834 58 627.618

Total 36421.662 59


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Interpretation:

For the second measure operating ratio, we have got the F value as 0.032. As the F value is less

than 3 it is not significant at 5% level. Therefore we accept the null hypothesis, which states

that there is no significant difference in the means of operating ratio of small and large size

firms and reject the alternative hypothesis, which states that there is significant difference in

the means of operating ratio of small and large size firm.

Asset Turnover Ratio TABLE-11


Between Groups 2.02E-04 1 2.02E-04 0.001

Within Groups 22.89 58 0.395

Total 22.89 59

Interpretation:

For the third measure asset turn over ratio, we have got the F value as 0.001. As the F value is

less than 3 it is not significant at 5% level. Therefore we accept the null hypothesis, which

states that there is no significant difference in the means of asset turn over ratio of small and

large size firms and reject the alternative hypothesis, which states that there is significant

difference in the means of asset turn over ratio of small and large size firm.


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Return On Capital Employed TABLE-12


Between Groups 30.437 1 30.437 0.084

Within Groups 21078.411 58 363.421

Total 21108.847 59

Interpretation:

For the fourth measure Return On Capital Employed we have got the F value as 0.084. As the

F value is less than 3 it is not significant at 5% level. Therefore we accept the null hypothesis,

which states that there is no significant difference in the means of Return On Capital Employed

of small and large size firms and reject the alternative hypothesis, which states that there is

significant difference in the means of Return On Capital Employed of small and large size

firm.

Debt Equity ratio TABLE-13




Total 106.58 59

Interpretation:

For the fifth measure Debt Equity ratio, we have got the F value as 0.036. As the F value is less


that there is no significant difference in the means of Debt Equity ratio of small and large size

firms and reject the alternative hypothesis, which states that there is significant difference in

the means of Debt Equity ratio of small and large size firm.


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Interest Coverage ratio TABLE-14


Between Groups 26.125 1 26.125 0.002

Within Groups 899150.062 58 15502.587

Total 899176.187 59

Interpretation:

For the sixth measure Interest Coverage ratio, we have got the F value as 0.002. As the F value

is less than 3 it is not significant at 5% level. Therefore we accept the null hypothesis, which

states that there is no significant difference in the means of Interest Coverage ratio of small and


difference in the means of Interest Coverage ratio of small and large size firm.

Current Ratio TABLE-15


Between Groups 0.12 1 0.12 0.056


Total 125.214 59

Interpretation:

For the seventh measure current ratio, we have got the F value as 0.056 As the F value is less


that there is no significant difference in the means of current ratio of small and large size firms

and reject the alternative hypothesis, which states that there is significant difference in the

means of current ratio of small and large size firm.


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Dividend Payout ratio TABLE-16


Between Groups 168.291 1 168.291 0.655

Within Groups 14912.41 58 257.111

Total 15080.701 59

Interpretation:

For the eight measure Dividend Payout ratio, we have got the F value as 0.655 As the F value

is less than 3 it is not significant at 5% level. Therefore we accept the null hypothesis, which

states that there is no significant difference in the means of Dividend Payout ratio of small and


difference in the means of Dividend Payout ratio of small and large size firm.

Book Equity to Market Equity TABLE-17


Between Groups 11.323 1 11.323 2.745


Total 250.582 59

Interpretation:

For the ninth measure Book Equity to Market Equity ratio, we have got the F value as 2.745 As

the F value is closer to 3 it is significant at 5% level. Therefore we reject the null hypothesis,

which states that there is no significant difference in the means of Book Equity to Market

Equity ratio of small and large size firms and accept the alternative hypothesis, which states

that there is significant difference in the means of Book Equity to Market Equity ratio of small

and large size firm.


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Earnings ratio TABLE-18



Within Groups 3.195 58 5.51E-02

Total 3.221 59

Interpretation:

For the earnings ratio, we have got the F value as 0.473, As the F value is less than 3 it is not

significant at 5% level. Therefore we accept the null hypothesis, which states that there is no

significant difference in the means of earnings ratio of small and large size firms and reject the

alternative hypothesis, which states that there is significant difference in the means of earnings

ratio of small and large size firm.

Cash EPS TABLE-19


Between Groups 0.155 1 0.155 1.247


Total 7.383 59

Interpretation:

For the Cash EPS measure, we have got the F value as 1.247 As the F value is less than 3 it is

not significant at 5% level. Therefore we accept the null hypothesis, which states that there is

no significant difference in the means of Cash EPS of small and large size firms and reject the

alternative hypothesis, which states that there is significant difference in the means of Cash

EPS of small and large size firm.


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Traded Quantity TABLE-20


Between Groups 2.23778E+13 1 2.23778E+13 8.075

Within Groups 1.60734E+14 58 2.77128E+12

Total 1.83112E+14 59

Interpretation:

For the last measure Traded Quantity ,we have got the F value as 8.075 As the F value is

greater than 3 it is significant at 5% level. Therefore we reject the null hypothesis, which statesthat there is no significant difference in the means of Traded Quantity of small and large size

firms and accept the alternative hypothesis, which states that there is significant difference in

the means of Traded Quantity of small and large size firm.


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Kruskal-Wallis Test

Institutional Investors TABLE-21

Ranks

VAR00002 N Mean Rank

VAR00001 0 30 37.53

1 30 23.47

Total 60

Test Statistics

VAR00001

Chi-Square 9.731

df 1

Asymp. Sig. 0.002

Interpretation:

Among the various measures tested, for institutional investor share we have got the Chi-Square

value as 9.73. As the Chi-Square value is greater than 3 it is significant at 5% level. Therefore

we reject the null hypothesis and accept the alternative hypothesis, which states that there is

significant difference in the means of institutional ownership holdings of small and large size

firms and also we found that stocks of small firms are more neglected by institutional investors

than those of large firms.

Operating Ratio TABLE-22

Ranks


VAR00001 0 30 30.9

1 30 30.1

Total 60

Test Statistics

VAR00001

Chi-Square 0.031

df 1

Asymp. Sig. 0.859


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Interpretation:

For the second measure operating ratio, we have got the Chi-Square value as 0.031. As the

Chi-Square value is less than 3 it is not significant at 5% level. Therefore we accept the null

hypothesis, which states that there is no significant difference in the means of operating ratio of

small and large size firms and reject the alternative hypothesis, which states that there is

significant difference in the means of operating ratio of small and large size firm.

Asset Turnover Ratio TABLE-23

Ranks


VAR00001 0 30 28.45

1 30 32.55

Total 60

Test Statistics

VAR00001

Chi-Square 0.827

df 1

Asymp. Sig. 0.363

Interpretation:

For the third measure asset turn over ratio, we have got the Chi-Square value as 0.827. As the


hypothesis, which states that there is no significant difference in the means of asset turn over

ratio of small and large size firms and reject the alternative hypothesis, which states that there

is significant difference in the means of asset turn over ratio of small and large size firm.


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Return on Capital Employed TABLE-24

Ranks


VAR00001 0 30 31.53

1 30 29.47

Total 60

Test Statistics

VAR00001

Chi-Square 0.21

df 1

Asymp. Sig. 0.647

Interpretation:

For the fourth measure Return On Capital Employed we have got the Chi-Square value as

0.021. As the Chi-Square value is less than 3 it is not significant at 5% level. Therefore we

accept the null hypothesis, which states that there is no significant difference in the means of

Return On Capital Employed of small and large size firms and reject the alternative hypothesis,

which states that there is significant difference in the means of Return On Capital Employed of

small and large size firm.


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Debt Equity TABLE-25

Ranks


VAR00001 0 30 28.43

1 30 32.57

Total 60

Test Statistics

VAR00001

Chi-Square 0.84

df 1

Asymp. Sig. 0.359

Interpretation:

For the fifth measure Debt Equity ratio, we have got the Chi-Square value as 0.084. As the


hypothesis, which states that there is no significant difference in the means of Debt Equity ratio


significant difference in the means of Debt Equity ratio of small and large size firm.


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Interest Coverage TABLE-26

Ranks


VAR00001 0 30 32.97

1 30 28.03

Total 60

Test Statistics

VAR00001

Chi-Square 1.197

df 1

Asymp. Sig. 0.274

Interpretation:

For the sixth measure Interest Coverage ratio, we have got the Chi-Square value as 1.197. As

the Chi-Square value is less than 3 it is not significant at 5% level. Therefore we accept the null

hypothesis, which states that there is no significant difference in the means of InterestCoverage ratio of small and large size firms and reject the alternative hypothesis, which states

that there is significant difference in the means of Interest Coverage ratio of small and large

size firm.


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Current Ratio TABLE-27

Ranks


VAR00001 0 30 27.2

1 30 33.8

Total 60

Test Statistics

VAR00001

Chi-Square 2.142

df 1

Asymp. Sig. 0.143

Interpretation:

For the seventh measure current ratio, we have got the Chi-Square value as 2.142 As the Chi-

Square value is less than 3 it is not significant at 5% level. Therefore we accept the null

hypothesis, which states that there is no significant difference in the means of current ratio of

small and large size firms and reject the alternative hypothesis, which states that there is

significant difference in the means of current ratio of small and large size firm.


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Dividend Payout TABLE-28

Ranks


VAR00001 0 30 31.43

1 30 29.57

Total 60

Test Statistics

VAR00001

Chi-Square 0.171

df 1

Asymp. Sig. 0.679

Interpretation:

For the eighth measure Dividend Payout ratio, we have got the Chi-Square value as 0.171 As

the Chi-Square value is less than 3 it is not significant at 5% level. Therefore we accept the null

hypothesis, which states that there is no significant difference in the means of Dividend Payout

ratio of small and large size firms and reject the alternative hypothesis, which states that there

is significant difference in the means of Dividend Payout ratio of small and large size firm.


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Book Equity to Market Equity TABLE-29

Ranks


VAR00001 0 30 26.63

1 30 34.37

Total 60

Test Statistics

VAR00001

Chi-Square 2.941

df 1

Asymp. Sig. 0.086

Interpretation:

For the ninth measure Book Equity to Market Equity ratio, we have got the Chi-Square value

as 2.941 As the Chi-Square value is closer to 3 it is significant at 5% level. Therefore we reject

the null hypothesis, which states that there is no significant difference in the means of Book

Equity to Market Equity ratio of small and large size firms and accept the alternative

hypothesis, which states that there is significant difference in the means of Book Equity to

Market Equity ratio of small and large size firm.


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Earnings TABLE-30

Ranks


VAR00001 0 30 26.55

1 30 34.45

Total 60

Test Statistics

VAR00001

Chi-Square 3.07

df 1

Asymp. Sig. 0.08

Interpretation:

For the earnings ratio, we have got the Chi-Square value as 3.07, As the Chi-Square value is

greater than 3 it is significant at 5% level. Therefore we reject the null hypothesis, which states

that there is no significant difference in the means of earnings ratio of small and large size


the means of earnings ratio of small and large size firm.


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Cash EPS TABLE-31

Ranks


VAR00001 0 30 26.68

1 30 34.32

Total 60

Test Statistics

VAR00001

Chi-Square 2.867

df 1

Asymp. Sig. 0.09Interpretation:

For the Cash EPS measure, we have got the Chi-Square value as 2.867. As the Chi-Square

value is closer to 3 it is significant at 5% level. Therefore we reject the null hypothesis, which

states that there is no significant difference in the means of Cash EPS of small and large size


the means of Cash EPS of small and large size firm.

Traded Quantity TABLE-32

Ranks


VAR00001 0 30 39.8

1 30 21.2

Total 60

Test Statistics

VAR00001

Chi-Square 17.014

df 1

Asymp. Sig. 0


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Interpretation:

For the last measure Traded Quantity, we have got the Chi-Square value as 8.075 As the Chi-

Square value is greater than 3 it is significant at 5% level. Therefore we reject the null

hypothesis, which states that there is no significant difference in the means of Traded Quantity


significant difference in the means of Traded Quantity of small and large size firm.


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Conclusion:

Initially ANOVA a parametric test has been used to test for significance of the differences

among means of various measures. Among the various measures for institutional negligence

we got the f value 10.059 at 5% significance level. It shows that small firms and large firms

are significantly differing in their means of institutional ownership holdings and we found that

stocks of small firms are more neglected by institutional investors than those of large firms.

Second measure book equity to market equity gives the f value of 2.745 that small firms and

large firms are significantly differ. This measure shows the distress level, higher book equity to

market equity greater the distress level. Small firms have greater book equity to market equity

than large firms.

Third measure average traded quantity also gives the f value of 8.075 at 0.006 level of

significance we can easily interpret that means are significantly differ and large firms stocks

are more frequently traded than those of small firms stocks.

Fourth measure cash EPS gives the f value 1.24 at 0/269 level of significance. Other measures

such as operating ratio, asset turnover ratio, return on capital employed, debt equity, interest

coverage, and current ratio. Dividend payout earnings ratios also included and obtained the fvalues 0.032, 0.001, 0.084, 0.036, 0.002, 0.056, 0.655, 0.473 respectively but these measures

are not showing significant difference among their means.

Out of twelve measures we found that three measures accept alternative hypothesis which

states that the operating, financial and liquidity characteristics substantially differentiates

small firms from the larger ones. where as other nine measures accept the null hypothesis

which states that the operating, financial and liquidity characteristics does not substantially

differentiates small firms from the larger ones.

Then a non parametric test KRUSKAL-WALLIS test is used to test the differences among

means of different variables in this test we got the chi-square value 9.731 at 5% significance

level for institutional negligence. Here also means of two samples are significantly differ.


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Second measure book equity to market equity gives the chi-square value 2.941 at 5% level of

significance. We can interpret that means are different and small firms are more distressed than

large firms.

Third measure average traded quantity gives the chi-square value 17.014 highest among tall the

measures at 5% level of significance large firms stocks are more liquid than small firms stocks.

Fourth measure earnings per share measure give the chi-square value 3.07 at 5% level of

significance. Cash EPS measure also gives chi-square value 2.867 also significantly differ in

the means of small firms stocks and large firms stocks.

Operating ratio, asset turnover ratio, return on capital employed, debt equity, interest coverage,

current ratio. Dividend to payout give chi-square values 0.031, 0.827, 0.21, 0.84, 1.197, 2.142,

0.171 respectively these measures doesnt differ significantly in the means of small firms and

large firms stocks.

Out of twelve measures we found that four measures accept alternative hypothesis which states

that the operating, financial and liquidity characteristics substantially differentiates small firms

from the larger ones. where as other eight measures accept the null hypothesis which states that

the operating, financial and liquidity characteristics does not substantially differentiates small

firms from the larger ones.

Table-33 showing Acceptance and Rejection of Null and Alternative Hypothesis

of different measures.

MeasuresF value

CalculatedTable Value

at 5%Null

HypothesisalternativeHypothesis

InstitutionalInvestors Share 10.059 3.14 Reject Accept


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operating profit ratio 0.032 3.14 Accept Reject

asset turnover ratio 0.001 3.14 Accept Reject

Return On CapitalEmployed 0.084 3.14 Accept Reject

Debt Equity 0.036 3.14 Accept Reject

Interest CoverageRatio 0.002 3.14 Accept Reject

Current Ratio 0.056 3.14 Accept Reject

Dividend Payout Ratio 0.655 3.14 Accept Reject

Book Equity to MarketEquity 2.745 3.14 Accept Reject

Earnings 0.473 3.14 Accept Reject

Cash EPS 1.247 3.14 Accept Reject

Traded Quantity 8.075 3.14 Reject Accept

To conclude,

The stocks of small firms are significantly less liquid and more neglected by institutional

investors than those of large firms. Small firms have low operating profitability and higher

financial leverage (as revealed by debt equity ratio). Moreover small firms are highly

distressed firms as slow by their high book equity to market equity ratio.

The study shows that the small firms differ from large firms owing to risk characteristics

reflected by the following five measures average daily trading volume, institutional neglect,book equity to market equity ratio. Debt equity ratio. And operating profit ratio.

Glossary:

Risk-Degree of uncertainty of return on an asset.

Risk Premium -excess return or extra reward for assuming risks.


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Systematic Risk-Risk common to a particular sector or country. Often refers to a risk resulting

from a particular "system" that is in place, such as the regulator framework for monitoring of

financial institutions.

Beta- The measure of an assets risk in relation to the market (for example, Nifty the) or to

alternative benchmark.

Specific risk - Also called unsystematic risk or idiosyncratic risk. Specific company risk that

can be eliminated through diversification.

Bibliography

1. Statistical methods- Levin and Rubin

2. Investments-Marcus

3. Investment management- V.K.Bhalla


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4. Applied finance

5. Rolf W Banz: Relationship between Return and Market value of Common stocks :

March 1981 ,Journal of financial economics volume 9.

6. Christopher James and Robert o Edmister:-The Relationship between Common

Stock Returns, Trading Activity and Market Value September 1983, Journal of

finance volume 38

7. K.C Chan:-An Exploratory Investigation of the Firm Size Effect 1985, Journal of

financial economics, volume 14.

8. Vijay B, AV vedpuriswar:-Small Firm Effect in the Indian Stock Market an

Empirical Study

July 2002, journal of applied finance, volume 8

Documents

Sources of Size Effect-Evidence From the Indian Stock Market-Santhosh Kumar S-0499