THE EFFECT OF MACROECONOMIC VARIABLES ON STOCK MARKET PERFORMANCE: A CASE STUDY OF GHANA

SAMUEL DAGADU

Subject Area: Finance & Economics

Submitted: February 2010

Dissertation submitted to University of Leicester in partial fulfilment of the requirements for the degree of Master of Science in Finance.

Table of ContentsAcknowledgments Executive Summary 1.0 Introduction 1.1 1.2 1.3 Macroeconomic factors and Stock market returns The Role of Governments The Economy of Ghana 1.3.1 1.3.2 1.3.3 1.3.4 1.3.5 1.4 1.5 1.6 1.7 1.8 2.0 2.1 The Recent Developments Oil Revenue Expectation Macroeconomic Trends (2000 to 2009) Economic Policies Policy Implementation Experience 9 9 10 11 11 12 13 17 18 19 21 22 23 24 25 25

The Ghana Stock Exchange Other Institutions of Importance: The Bank of Ghana Research Questions Interest in Research Structure of Dissertation Macroeconomic factors that affect Stock Market Returns 2.2 Models used to establish relationship between

Literature Review

macroeconomic factors and stock returns 2.3 2.4 Previous research on Ghana Stock Exchange Theoretical considerations 2.4.1 Interest rates 2.4.2 Inflation 2.4.3 Fiscal deficits/surpluses 2.4.4 Exchange rates 2.4.5 Gross Domestic Product (GDP)

27 29 30 30 31 31 32 33

2

2.4.6 The Role of Government

35

3.0

Methodology 3.1 3.2 3.3 3.4 Data Collection Variable selection Model specification Tests conducted 3.4.1 Visual Inspection 3.4.2 Unit Roots Tests 3.4.3 Co integration Tests 3.4.4 Vector Error Correction 3.4.5 Granger Causality Tests 3.5 3.6 Data description Regression

37 37 37 39 40 40 40 41 42 42 45 45 45 46 47 48 48 48 49 49 50 53 54 55 58 61 62 3

3.7.0 Hypothesis 3.7.1 Interest rates 3.7.2 Inflation 3.7.3 Exchange rate 3.7.4 Fiscal deficits/surpluses 3.7.5 Gross Domestic Product 4.0 Data Analysis 4.1 4.2 4.3 4.4 5.0 6.0 7.0 8.0 Unit Roots Test Co-integration Vector Error Correction Granger Causality

Research Findings Conclusion Recommendation Reflection

9.0

References

65 70-103

10.0 Appendices

ACKNOWLEDGEMENTSI would like to thank Dr. Tomasz Wisniewski of University of Leicester, for his guidance and advice on topic selection. I also thank Dr. Tse, University of Leicester, for his advice, guidance and support from the proposal stage through to final submission. My appreciation also goes to my employer, Social Security and National Insurance Trust for sponsoring my studies, to Mr. Kwasi Boaten - Former Director General and Sheila Sampson, Training Manager, for their interest in my studies. My appreciation and thanks goes to my Superiors, Colleagues and Subordinates for their support during the period of my studies. I thank Dr. E. E. Y Dagadu for his support and encouragement throughout my career development and for buying the econometrics software used for the analysis. I finally wish to thank my immediate family Bridget, Teddy, Jeffrey, Jennifer, Harold and Philip for their support, patience and understanding during the period of my studies. It would have been impossible to complete my dissertation without their involvement. I owe a debt of gratitude to Mr. Simon Dewotor and his family for mentoring me and showing me the path to success.

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Executive Summary This study examines the long and short run relationships between

macroeconomic variables and stock market returns in general using Ghana Stock Exchange Index as a special case, to find answers to the following questions: What macroeconomic factors drive the performance of Ghana Stock Index? How does GDP, Fiscal balance, Inflation, Interest rates and Exchange rates impact the Ghana Stock Index (GSI)? The macroeconomic variables used for this study are Gross Domestic Product (GDP), Fiscal balance (deficit/surpluses), Inflation, Interest rates and Exchange rates. Finding answers to these questions will help add to existing knowledge about the underlying causes of price movements of the Ghana Stock Exchange and how these variables can be useful in predicting the performance of the Ghana Stock Exchange. This study was undertaken in partial fulfilment of the requirements for the award of degree of Master of Science in Finance, University of Leicester. There is no economic theory that explains the linkage between macroeconomic variables and stock market performance in one direction, but there are several macroeconomic factors that have been identified as having impact on stock market performance. This study used the Dividend Discount Model to select the variables considered in the study.

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Cointegration, Error Correction and Granger causality techniques were used to establish relationships. The long term relationships were analysed and established by Johansen and Juselius Multivariate Co integration Approach. Short term relationships were analysed and established through Vector Error Correction models and Granger Causality tests. Monthly time series data from January 1991 to December 2008 were used. Data on Fiscal balance, Inflation, 91 day Treasury bill rates and Exchange rates movements were obtained from the Bank of Ghana and stock Index movements were obtained from the Ghana Stock Exchange. Empirical findings revealed that macroeconomic variables considered are cointegrated and have statistically significant coefficients that indicate the existence of long term relationships. The strength of relationship in the short run is however weak indicating the variables do not have short term relationship. The results indicate that the Ghana Stock Market has significant positive long run relationship with GDP and Inflation but negative long run relationship with fiscal deficit, interest rates and exchange rates. These results are consistent with current theoretical arguments regarding these relationships. The results are in line with anticipated relationships between the variables, with the exception of Inflation, which shows a positive instead of negative relationship. The policy relevance of this study is significant now and into the future because the economic policy of Ghana is geared towards growth and stability. The Country is expecting the production and export of crude oil. GDP is projected to grow from 5% in 2010 to 24.2 % in 20111. The commencement of oil production will create serious macroeconomic imbalance which needs to be managed carefully to ensure sustainable growth and stability. Moreover, individuals, Pension Funds and Institutional Investors invest on the Stock market to ensure a future stream of income. Any erosion of capital in the market due to1

IMF Country Report No.9/256, August 2009 6

macroeconomic imbalances can have dire consequences for all market participants. This study will be useful in formulating both fiscal and monetary policies. Other studies on the Ghana Stock Exchange reported on the impact of inflation, interest rates, foreign direct investments and exchange rates. No study considered the effect of GDP and Fiscal imbalances on the Ghanaian Stock Index. This paper is therefore adding to the body of knowledge on the relationship between these macroeconomic variables and stock market returns in Ghana. The lag length used for the error correction in this study may be a limitation and might have accounted for the disparity in results when this study is compared with other studies conducted on the GSI. The slow pace of adjustment suggests that the macroeconomic factors examined in this study are not exhaustive. There may be other significant factors which were not considered in this study. Another limitation is the lack of monthly data for some of the variables. This may be a contributory factor in the lag length required for the variables to relate to each. The Government of Ghana is concerned about stability and growth. Greater stability can be achieved if the Government of Ghana establishes the following through the Bank of Ghana and the Ministry of Finance. Stable monetary growth to match the future growth potential of the economy; Manage money supply with the hope of maintaining prices; Maintain fiscal deficit or surpluses during periods of recession and periods of expansion respectively; Automatic stabilizers like unemployment benefits during periods of low economic activities, high corporate taxes during booms and low corporate taxes during recession, and wider coverage and progressive personal income tax regimes. The use of Oil revenue should also be regulated to avoid negative impact on macroeconomic variables.

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This study has contributed to existing knowledge on the grounds that there is a lag effect of changes in macroeconomic factors on the Ghanaian Economy in general and the Stock Exchange in particular. The transmission mechanism of policy needs further study to identify reasons for the lag and what can be done to correct it. For example, the current debate on radio and in the print media is for the Government to compel Banks to reduce their lending rates in line with reduction in inflation, prime rates and general improvement in other macroeconomic factors.

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1.0

Introduction

The Ghana Stock Exchange experienced a highly volatile performance since it was established in 1990. It was pronounced the best performing stock exchange in the World in 2004. It performed above 100% in the following years 1993, 1994, 2003 and performed below 0% (zero) in the following years 1990, 1991, 1992, 1999, 2005 and 2009. The causes of these fluctuations in performance can be attributed to the changes in macroeconomic factors from theoretical and empirical point of view but not by merely looking at the movement of macroeconomic variables. The GSE performance is measured by GSE AllShare- Index, which is a market value weighted index. 1.1 Macroeconomic factors and Stock market returns

Macroeconomic variables have significant effect on stock price movement and returns but the basis of the causal relationship between macroeconomic variables and stock prices is not known with certainty as indicated by Flannery and Protopapadakis (2002). Efficient market hypothesis attributes movement of stock prices to new information that affect the expected discount rates or future income. An efficient market, for example, incorporates all current market information in stock prices. Any new information is captured instantaneously to reflect all available information. Studies by Fama and Schwert (1977), and Jaffe and Mandelker (1976) suggest that new information on macroeconomic factors have an impact on stock prices. This affirms the belief that macroeconomic variables influence stock returns and thus proposes that stock markets are not

9

efficient. Empirical evidence suggests that stock returns respond to monetary news but there is no theory on the relationship of stock returns with macroeconomic variables in one direction, even though stock prices are known to react to market forces. Uncertainty remained about relationships between macroeconomic variables and stock performance because of varying economic conditions of nations, different data set and different testing methods used to establish these relationships. Economic factors that impact on changing investment opportunities; the pricing polices; and factors which affect dividends theoretically, impact pricing and performance of stock exchanges. Predictability of stock market returns using macroeconomic factors suggests that markets are not efficient. As indicated by Fama (1991), stock prices reflect expectations of earnings, dividends, interest rates and future economic activity. If stock prices reflect the underlying fundamentals, then we can say that there is a causal relationship between macroeconomic variables and stock prices. Participants in the stock market anticipate real returns from the stock market so stock prices will move directly with inflation. Investors directly compare earning yield on stocks with treasury yields and move funds from one market to the other, an inverse relationship between stock returns and interest rates is expected. Fiscal deficits increase Government borrowing which increases interest rates, which crowd out private individuals and businesses, denying listed companies of much needed capital resulting in low returns. 1.2 Role of Governments

Twerefou and Nimo (2005) reported that businesses factored into their operations Government macroeconomic targets for the year. This invariably feeds into the determination of stock prices of listed companies. Twerefou and Nimo (2005:169). Governments fiscal and monetary policies have significant effect on the economy and therefore the capital market. Fiscal policy is aimed at consumer demand in an effort to manage economic growth. Tax cuts encourage

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demand and for that matter spending. Tax increases discourage spending and slow down the economy. Governments debt financing causes interest rates to rise and this directly causes Inflation and depreciation of the local currency. Depreciation results in capital flights. Investors who do not have confidence in the economy divert resources from the long term investments to short term treasury bills and consumables or real estate. Listed Companies are starved of needed resources to finance viable projects, since they cannot borrow at the prevailing high interest rates, they become less competitive and their profit levels fall leading to a fall in returns. The Government of Ghana has a key role to play in ensuring a sound capital market through macroeconomic measures such as the fiscal environmenttaxation; legal, regulatory and institutional infrastructure, as well as monetary policies. Other factors like oil price hikes, change of Governments, international financial and economic development/crises also have impact on the economy but these factors were not considered in this study. 1.3 The Economy of Ghana

1.3.1 The Recent Developments Ghana went through a keenly contested democratic election in December 2008. The National Democratic Party took over from the New Patriotic Party, which was in Government for the past eight (8) years, in January 2009. The new Government adopted a program of macroeconomic stabilization and growth through reforms in joint partnership and support with the International Monetary Fund (IMF).

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The real GDP growth somewhat consistently increased from 3.7% in 2000 to 7.3% in 2008 on the back drop of significant debt relief and strong commodity prices which gave some fiscal relief to the country in its developmental efforts, leading to higher output, declining Inflation, and poverty reduction. The improved macroeconomic environment enabled Ghana to raise US$750 million in Eurobonds in October 2007 for infrastructural development in the energy sector in particular. Important institutional reforms have been undertaken in the financial sector to safeguard the stability of the financial system but the nation suffered a severe energy crisis in 2006-2007 as a result of prolonged drought, which lead to near shutdown of Akosombo Hydro Electric generating plant. This resulted in a shift in over dependence on hydro power to thermal power at the time of rising crude oil prices creating macroeconomic pressure on the economy. The global food and fuel price increases of 2007-2008 hit Ghana very hard. The government implemented some social mitigation policies which dampened the effects of the global food crises. 1.3.2 Oil Revenue Expectation Ghana discovered crude oil along Cape Three Points in fields named the Jubilee fields. The dominant players are Tullow Oil Plc and Kosmos Energy Plc Companies. The Ghana National Petroleum Company (GNPC) is also in collaboration with some Chinese and other oil exploration companies that are prospecting for oil and gas in five sedimentary basins including inland Voltaian, offshore Tano and Saltpond basins. It is expected that drilling in commercial quantities from the Jubilee fields will commence by the last quarter of 2010. Daily production is expected to be 120,000 barrels until the end of 2012 when the expected production target is 250,000 barrels per day. The Government of Ghana is making efforts to create policies and frameworks that will ensure maximum gains from the oil industry. Particular concerns are how much to save,

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how much to spend on what, in order to insulate the economy against fiscal fluctuations, and to protect the economy against exchange rate appreciation. Other concerns are environmental protection, technological transfers and the avoidance of the Dutch disease. The projected direct annual oil revenue is 7% of 2008 GDP and about 26% of 2008 domestic revenue. IMF projects 4% to 5% of annual revenue as indicated by ISSER Report (2008). This is indeed a substantial injection. It however, excludes revenue from Gas, which is currently controlled domestically, and downstream industries that will spring up as a result of the oil Industry. 1.3.3 Macroeconomic Trends (2000-2009)

Ghana experienced macroeconomic instability for many years in the past. This affected growth of the economy. The Country achieved significant gains in the macroeconomic and social sectors from 2000 to 2005. The past four (4) years however experienced imbalances, caused by the energy crises of 2006-2007 and external shocks resulting from rising food and oil prices. This was compounded by the 2008 general elections because of increased direct and indirect election related expenses and energy related subsidies, higher wages and salaries among others. All these culminated in raising fiscal deficits from 7.81% of GDP in 2006 to 11.48% in 2008 and 10.7% in 2009. The global financial crises contributed to balance of payment pressures in the face of reducing private remittances and outflow of portfolio investment proceeds. The exchange rate plummeted from mid 2008 to June 2009. The rate of depreciation slowed down because of injection of foreign currency into the economy by IMF. The cedi weakened against all the major trading currencies like the Dollar, the Pound Sterling and the Euro. The Bank of Ghana set a minimum capital requirement of GH60 million for Banks by the end of 2009. Domestic Banks are however required to increase

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their capital to GH25 million by the end of 2010 and then to GH60 million by the end of 2012. The National Pensions Act of 2008 came into effect in January 2010; it provided the frame work for a three tier pension system. The first tier is run by Social Security and National Insurance Trust (SSNIT). The Occupational Pension Schemes and Private Pension schemes are run by Trustees who appoint Fund Managers and Custodians. They all operate under the regulatory regime of a Pensions Authority. The Pension Authority is expected to ensure that Pension funds are prudently managed. It is expected that there will be an injection of capital in the system for speculative and investment activities. Table 1 shows the trend in some macroeconomic variables from 1993 to 2009. Table 1 Trends of Macroeconomic variables & Chart 1Market Returns% Real GDP% Fiscal bal as % of GDP91 day T/Bills

YEAR 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Interest%

Inflation%

% GHS/ USD

113.74 124.34 6.33 13.82 41.85 69.19 (15.22) 16.55 11.42 45.96 154.67 91.33 (29.85) 4.97 31.84 58.06 (46.52) 4.7*

5.00 3.30 4.00 4.60 4.20 4.70 4.40 3.70 4.20 4.50 5.20 5.60 5.90 6.40 5.70 7.3010.7*

(2.65) 2.26 0.95 (3.16) (8.21) (6.07) (6.51) (8.62) (4.36) (6.11) (3.52) (2.77) (1.95) (7.81) (8.10) (11.48)

32.00 28.38 36.50 41.98 42.73 34.28 26.36 39.10 40.99 25.10 28.80 17.28 15.43 10.16 9.92 17.79 23.52

70.80 32.70 20.80 15.70 13.80 18.19 4.94 40.20 43.49 9.49 29.76 18.18 15.48 10.96 10.72 16.46 19.30

(13.13) 155.11 (27.46) 36.28 25.21 12.89 15.21 104.61 31.43 10.62 9.65 3.53 0.77 1.12 1.98 13.0518.11

Source: Bank of Ghana & Ghana Stock Exchange * Estimates.

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160

120

80

40

0

-40 1992

1994

1996

1998

2000

2002

2004

2006

2008

M/Returns% Fiscal% Inflation%

GDP% Interest% Dollar%

15

M/Returns%160 120 80 40 0 -40 92 94 96 98 00 02 04 06 08 8 7 6 5 4 3 92 94 96 98

GDP%

00

02

04

06

08

Fiscal%4 50 40 30 -4 20 -8 10 0 92 94 96 98 00 02 04 06 08 92 94 96

Interest%

0

-12

98

00

02

04

06

08

Inflation%80 160 120 80 40 40 20 0 -40 92 94 96 98 00 02 04 06 08 92 94 96 98

Dollar%

60

0

00

02

04

06

08

16

1.3.4 Economic Policy The Government of Ghana is pursuing economic policies that will ensure the attainment of macroeconomic stability and growth. The strategy is being accomplished through fiscal discipline and programs geared towards prudent public expenditure management, enhanced domestic revenue mobilization, enforcement of public procurement laws and restructuring of utility companies to reduce subsidy on the consolidated budget from these utilities. Public sector reforms are also being under taken to bring on board a single spine salary structure. The Government intends to reduce the budget deficit through cuts in low priority public expenditures in order to reduce total public expenditure in relation to GDP. Revenue mobilization was to be strengthened to increase revenues in relation to GDP. Monetary Policy support Governments fiscal consolidation efforts with emphasis on price stabilization and growth as well as exchange rate expectation. This is done through inflation targeting which is a framework by which policies are guided by the expected path of future inflation relative to already planned and announced inflation target. The Ghana Poverty Reduction Strategy (GPRS II) has at its base the provision of a life line scheme to mitigate the risks non income earners or low-income vulnerable groups face. The Livelihood Empowerment Against Poverty (LEAP) cash transfer program, school feeding and free maternal care programs, capitation grant and youth in employment programs, provision of free exercise books and free school uniforms for school pupils in deprived communities are examples of mitigating factors in place.

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1.3.5 Policy Implementation Experience Maintaining fiscal discipline has been and is still a major challenge for all Governments of Ghana. Ghana has a well thought out fiscal and monetary policy but the policy transmission mechanism has some challenges largely because of implementation. Implementation of economic policy is difficult because of lags between the time policy makers identify the problem and when decisions are made as well as when the decisions are implemented as against when the full impact is felt, the impact of unanticipated changes is greater than that of anticipated changes. Inflation targeting for instance is based on expected future inflation. This may suffer from recognition lag, which is the time it takes for policy makers to recognize that an economic change which needs a policy change has occurred. Inflation for example can assume a downward trend while discount rates and particularly Bank base rates will either remain stable or be on the increase as the economy of Ghana experienced in the past and currently. Implementation time lag is shorter for monetary policy than fiscal policy. The Monetary Policy Committee of Bank of Ghana meets frequently to determine the Prime rate on which interest rates and inflation targeting is based, but fiscal policy needs approval from Parliament. The impact lag is however shorter for fiscal policy than monetary policy. Economic policy based on past events creates certain errors depending on whether the policy is based on adaptive expectation or on rational expectation. Adaptive expectation yield systematic errors resulting in over or under estimation. Inflation targeting policy is based on rational expectation, considers the future and currently available information instead of historical data. Random forecasting errors are made but the problem is the time lags and whether the policy change is expected or not. Expected monetary and fiscal policies have little or no impact

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on the economy as these factors might have been factored in prices or budgets of companies. Unanticipated monetary policy changes have a greater impact. 1.4 The Ghana Stock Exchange

The Ghana Stock Exchange was established in July 1989 as a company limited by guarantee under the Companies code 1963. In October 1990, the Exchange was given recognition as an authorized Stock Exchange under the Stock Exchange Act of 1971 (Act 384). Trading commenced on the floor on 12th November 1990. The status of the Company changed from private to public company limited by guarantee in April 1994. The GSE is governed by a Council of representatives from licensed dealers, listed companies, banks, insurance companies, the money market and the general public. The exchange has been trading daily since mid 2008. . Prior to that, there were three (3) dealing dates every week. Trading activities are no longer done on the trading floor. A central securities depository has been established, securities have been dematerialized and trades are now done and settled electronically from Brokers offices. Dealers and the Investing public are required to register their shares online to be able to trade. The listing requirements include capital adequacy, profitability, efficiency of management, and float of shares and years of operational existence. The GSE performance is measured by GSE All- Share- Index, which is a market value weighted index. The GSE currently has 35 listed companies, one depository share and one preference share trading on the exchange actively. Two corporate Bonds, HFC and Standard Chartered Bank (SCB) Medium Term Bonds are also listed on the exchange. The HFC bonds will mature in March 2012. These bonds are dollar denominated with coupons priced at 6 months USD Libor +100bp. SCB Bonds matured in December 2009. The Government of Ghana has three categories of bonds, trading with terms of two (2) years, three (3) and five (5) years. The coupon rates range from (12.8%-21%), (12.08%-16%), and (13.67%-15%)

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respectively. The current yield on the other hand ranges from (12.64% to 17.11%) for 2 year bonds and (14.87% to 17.44%) for three year bonds. The listed shares are categorized into Manufacturing, Financial, Mining and Gas & Oil sub-sectors. The Bank of Ghana and Securities Exchange Commission are the regulators. The Ghana Stock Exchange achieved recognition in the global investment arena. In 2003 it achieved performance of 154.67% and was recognized as the best performing market in 2004. The remarkable performance was attributed to economic performance resulting from stable and good macroeconomic factors during the period leading to investor interest on the exchange. In 2008, Ghana Stock Exchange was adjudged one of the best during the period of financial meltdown of advanced markets. The remarkable performance was attributable to economic performance resulting from stable and strong macroeconomic factors. The feat of 2008 was to be followed by over 46% negative performance in 2009, the lowest in Africa. This poor performance was also attributed to poor macroeconomic factors by Market Analyst, a critical look at the performance figures suggests some lag of the effect of Macroeconomic factors on market performance. The good performance of the economy in 2005 to 2006/7 impacted the market in 2008. The poor performances in 2007 and 2008 impacted the market in 2009. It is difficult to say whether the Ghana Stock Exchange is efficient or not. It is difficult to depend on past price movement to make gains but the same cannot be said about the release of information. Some Companies announce good returns and prospects but nothing happens to their prices. This study does not consider the efficiency of the exchange.

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1.5

Institutions of Importance :The Bank of Ghana

The Bank of Ghana (BOG) is an independent body with oversight responsibility over the monetary policy and strategy of Ghana. The objectives of BOG include: Maintenance of the general price levels through implementation of monetary policy. Support the general economic policy of Government and promote economic growth Regulation of the financial sector of the economy The goals of monetary policy of Ghana include: Ensuring high levels of employment Economic growth Price stability Interest rate stability Financial Market Stability and Stability of the foreign exchange rate.

1.6

Research Questions

This paper does not test for market efficiency, but tries to establish short and long run relationships between various macroeconomic factors and stock returns using the Ghana Stock Index for stock market performance. Macroeconomic instability had negative effect on the Ghana Stock Exchange. It is not clear from available statistics and earlier studies on the Ghana Stock Exchange what macroeconomic factors or combinations of factors are responsible for the performance of the exchange. In 1993 for instance, Inflation rose to 70% when,

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the Interest rate was 30.95% and the Stock exchange recorded a performance rate of 116.06%. GDP grew in that year by 4.9%. In 1999, Inflation was as low as 21.3% and the Interest rate was as high as 34.19% but the stock performance was (15.14) % and GDP grew by 4.4%. The questions then are: 1: What macroeconomic factors drive the Ghana Stock Exchange? 2: How does GDP, Fiscal balance, Inflation rates, Interest rates and Exchange rates impact the Ghana Stock Index? Finding answers to these questions will help add to existing knowledge about the underlying causes of price movements of the Ghana Stock Index and how these variables can be used to predict market returns. It will be useful in giving policy guidelines to ensure stability of the capital market. It will also be a useful guide for Investors and Financial Analyst in assessing the price of stocks and their systematic risks with anticipated changes in the macroeconomic factors.

1.7

Interest in Research

This study is useful for Private Investors, Pension Funds, Government and policy makers because investments in equity have an assumption that corporate cash flows will grow with the economy, thus expected returns on equities may be linked to future economic performance. Macroeconomic factors impact both growth in the corporate sector and economy at large. Studying the relationship between macroeconomic factors and the stock market will assist in planning and predictability of both stock market and the economy. There is an emerging trend by which cohorts of investors lose their entire life time investment on stock markets or in Unit Trusts and Mutual Fund investments due to macroeconomic changes. Pensioners who expect lump sum payment from

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Unit Trusts and other Investment Companies on retirement are shocked when their entire life time investments are wiped out or drastically reduced mainly because of the risks associated with stock markets. As indicated by David Swensen (2000), equity biased asset allocation yield higher returns but it involves the acceptance of higher risks. It is necessary for Trustees of Pension Funds and other Fund managers to assess the risks involved at each turn of macroeconomic variables in order to maintain risk and return profile of their funds. The Government of Ghana and the Central Bank are concerned about stability and growth. This study attempts to identify how sustainable stability can be obtained. The interest of this study is to identify the possible macroeconomic variables that impact the stock returns and to examine whether these macroeconomic factors are the cause of fluctuations in stock market performance. I also want to recommend appropriate strategies to ensure that macroeconomic and fiscal policies of Governments do not affect Investors, particularly Pensioners, considering the fact that Ghana has now introduced defined contribution schemes which is based on individual equivalence as against risk pooling. This study was undertaken in fulfilment of the requirements for the award of degree of Master of Science in Finance, University of Leicester. 1.7 Structure of Dissertation

The remaining chapters of this study are arranged in this order: Section 2, reviews literature and theory in order to identify the variables of interest to this study and to examine the results of other studies. Section 3, introduces the data, describes the data and explains the techniques used to examine and measure relationship between macroeconomic variables and movements in stock returns. It considers theoretical and empirical justification for modeling the Ghana Stock Exchange All Share Index as a proxy using specific macroeconomic variables, as well as the conceptual framework and

23

methodology. Analysis of Data was done in section 4. Section 5 discusses the findings and interpretation of results. Section 6 gives a summary. Section 7, gives the conclusions and section 8 considers recommendations and section 9 gives summary of reflections and experience gathered during the period of the dissertation. The last sections detailed the references and appendices.

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2.0 2.1

LITERATURE REVIEW Macroeconomic factors and Stock Market Returns

According to Fama (1970), a stock market is efficient if current market prices fully and instantaneously reflect all available information about the macroeconomic fundamentals. Past information therefore contains no news so should have no effect on stock prices. Studies by Fama and Schwert (1977), Jaffe and Mandelker (1976) suggested that macroeconomic factors influence stock returns. Fama (1981), and Smith and Sims (1993) identified inflation, money supply, exchange rates as some of the major determinants of stock prices. Chen, Roll and Ross (1986) established the existence of long term equilibrium between stock prices and Inflation, Treasurybill rate, Long term government bonds and Industrial production. They highlighted the fact that, economic factors affected expected dividends and discount rates. The ability of firms to generate cash flows and payout dividends is the basis of the long term equilibrium between stock returns and macroeconomic factors. Discount rates change with the level of interest rates, term structure and risk premium, expected dividends may change due to changes in inflation rate, production, and consumption levels. Fama (1981), Bodie (1976) and other writers made a strong case that inflation has a negative relationship with stock performance because high inflation rates add to uncertainty which reduces business confidence and thus lowers stock prices. This is in direct contradiction to the claim that stocks are hedge against long term inflation as indicated by Anari and Kolari (2002). Humpe and Macmillan reported that deflation has resulted in poor stock market performance of Japan. Interest rates change the discount rate in the valuation model and so influence current and future cash flows. Mukhererjee and Naka (1995) hypothesized that

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changes in both short and long term interest rates will affect nominal risk free rates and so affect the discount rate. Fama and Schwert (1977) felt the relationship applies to both current period and for lagged observation of interest rates. Robert Pardy, (1992) emphasised the role of macroeconomic and fiscal environment in the development and performance of securities market. Corporate cash flows are related to a measure of aggregate output such as GDP or industrial production. Darrat and Mukherjee(1987), Mukherjee and Naka (1995) indicated that Stock Indexes are positively influenced by growth in GDP. Based on the fact that cash flows from firms are directly related to economic growth, Ritter (2004) argued that economic growth does not necessarily increase cash flow of existing stocks and stockholders. According to Ritter (2004) growth comes from high personal savings, increased labour force participation and technological change. If increases in capital and labour go into new corporations, it does to affect the cash flow of existing corporations. He continues that unless technological change comes from existing companies with monopoly power, it does not increase profits. It only increases per capita income of consumers. Many writers used Industrial production as a proxy of real economic activities. Fama (1990), Geske and Roll (1983) found positive relationship between Industrial Production and Stock returns through expected future cash flows. Some risks are involved in dollarisation of an economy as against the fact that investments are attractive when they are denominated in a stronger currency. Exchange rate appreciations are associated with higher investment leading to higher cash flows and higher stock performance. In an export oriented economy , as indicated by Mukherjee and Naka (1995) currency depreciations have positive relationship and impact the stock prices; deprecation of domestic currency leads to increase in demand of exports and cash flows. Currency appreciation, on the other hand, reduces competitiveness which results in a negative impact on the stock market.

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Some studies considered relationship between the same macroeconomic factors and stock markets in different Countries. Funke and Matsuda (2006) considered USA and Germany. Humpe and Macmillan compared US and Japan. They employed the discount valuation model. They found contrasting results in each country. Other studies considered macroeconomic and stock market relationships in developed Countries like USA, Germany, UK and Japan. Flannery and Propapadakis (2002) examined developed countries like USA, U.K and Japan, whilst other writers like Choudhry (2001), Wongbagpo and Sharma (2002) considered developing Countries. Poon and Taylor (1991) studied the effect of macroeconomic factors on UK stock prices and found that macroeconomic variables do not affect stock market prices. 2.2 Models used to establish relationships between macroeconomic factors and stock returns Ross (1976) linked macroeconomic variables and stock market returns through an Arbitrage Pricing Theory (APT) using statistical tools like factor analysis. APT did not specify the factors but were statistically derived. The factors were fundamental economic aggregates like GDP, Inflation and Interest rates but these factors were not stated by APT. Multiple risk factors were used to explain asset returns. ATP concentrated on individual stock returns. It involves modeling a short run relationship between macroeconomic variables and stock prices in terms of first differentials, with the assumption of stationarity of the underlying data. Relevant studies which used this approach include; Fama (1981), Fama and French (1989), Schwert (1990) among others. Chen, Roll and Ross (1986) established the existence of long term equilibrium using specific macroeconomic variables, from the perspective of efficient market

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theory and rational expectation and inter-temporal asset pricing theory. The macroeconomic factors were stated. The macroeconomic factors considered were Inflation, Treasurybill rate, Long term government bonds and Industrial production. The Discounted Cash flow model was also used to establish relationship between macroeconomic factors and stock returns. This model links stock prices to future expected cash flows and the future discount rate of these cash flows. All macroeconomic factors that influence future expected cash flows and discount rates have an influence on the stock price. This model was also used to establish long run relationships between stock prices and macroeconomic variables. Campbell and Shiller (1988) established that Price Earning ratio predict stock returns over long period of time. They used earnings and expected dividends to establish the relationship between these factors and stock prices. The limitation of this approach is that there is no theoretical basis for selection of the variables. Jiranyakul (2008) used Present Value Model on the Thailand Stock market from April 1975 to December 2007 to evaluate whether the current market price of each stock deviates from its intrinsic value (present value of stocks cash flows), from fundamental analysis. He concluded that there are other economic fundamentals other than dividends that cause stock price movements. Engel and Granger (1987), Granger (1986), Hendry (1986), Johansen and Juselius (1990), proposed the use of cointegration techniques and error correction models to establish long run and short run equilibrium between macroeconomic variables and stock market returns. Time series variables are cointegrated if they are integrated by the same order and a linear combination of all the variables is stationary. Linear combination of variables suggests the existence of long term relationship between the variables. The co-movement of the variables can be ascertained through error correction processes to establish short-term equilibrium. Cointegration and error correction models have been

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used extensively to establish both long run and short term relationship between stock prices and macroeconomic variables in both developed and developing countries. This approach has become the preferred method of examining the relationship between stock returns and macroeconomic variables as indicated by Maysami, Howe and Hamzah (2004) and Utku Utkulu(). This approach was used by many writers including Mukherjee and Naka (1995), Maysami (2002) among others. The number of lags used in these models, particularly the error correction model, has a great impact on the results. 2.3 Previous Research on Ghana Stock Exchange

Twerefou and Nimo (2005) investigated the impact of asset pricing of the various sectors of the Ghana Stock Exchange for the period January 1997 to December 2002 using Arbitrage Pricing Theory. They concluded that inflation, short term interest rates and term structure of interest rates are macroeconomic factors affecting asset pricing in Ghana. Adam, Anokye and Tweneboah, (2008), examined long and short run relationship between interest rate, inflation rate, net foreign direct investment, and exchange rate and the Ghana stock market during the period January 1991 to December 2006, using cointegration and error correction models. They concluded that there is long run relationship between stock prices and the macroeconomic factors examined. They found out that there is a positive relationship between inflation and share prices. Kyereboah-Coleman and Agyire-Tettey (2008) used quarterly time series data of the following macroeconomic factors: Inflation, real exchange rates, Interest rates, and lending rates to examine the effect of these macroeconomic factors on the performance of the Ghana Stock Exchange. They concluded that lending rates have an adverse effect on stock performance and Inflation had a lagged

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effect on stock performance. They were certain of the fact that depreciation favors investors. Frimpong (2009) used the cointegration model to establish long term relationship between exchange rates, the consumer price index, money supply, interest rates and stock returns of the Ghana Stock Exchange. He concluded that exchange rates have positive impact on the exchange while other variables have negative impact. These findings do not confirm each other mainly because of the lag period under consideration. Frimpong considered a lag period of nine (9) for cointegration analysis and lag of 3 for error correction. This study considers a lag period 10 to 15 for both cointegration and error correction.

2.4

Theoretical considerations

2.4.1 Interest rates Interest rates generally move in opposite direction with share prices. A fall in interest rates on money markets makes them less attractive in terms of returns. Investors generally react by transferring their investment to the stock market. This results in increase in demand for shares, this may lead to increases in prices. If interest rates increase on the other hand, investors may channel their current investments to the money markets thereby staving the stock exchange of the needed new investments. Trading activities therefore reduce as the market becomes bearish, as there are more shares on sale than buyers want, leading to fall in prices.

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Theoretically, Interest rates are not very significant in the determination of firms investment decisions because most firms base their investment decisions on the profit expectation of investments. Investments, with returns exceeding costs (positive NPV) will be undertaken. Fluctuation in interest rates will lead to lower real returns, which will eventually prevent investment in some projects, resulting in reduced flow of investments. Most firms however, do not borrow to finance investments. They use internal funds or issue new shares.

2.4.2 Inflation In theory, stocks should be inflation neutral. This is based on the assumption that companies can pass on one-for-costs. Secondly, the required rates Investors used to discount cash flows do not rise when inflation rises. Moreover it is assumed that inflation does not have long term impact of growth. There is a theory to support the fact that Inflation is a hedge against long term inflation as indicated by Anari and Kolari (2002), because it represents claims against real assets and so stock returns should be positively related to expected inflation. Another theory supports the idea that Inflation negatively impact on stock prices. This is based on Fishers theory of interest which indicated that nominal interest rates may be decomposed into real rates and expected inflation. The argument here is that expected real returns are determined by real factors which are not related to inflation. 2.4.3 Fiscal deficits/Surpluses The main source of revenue for Governments is taxation. Personal and corporate taxes move in the same direction as growth of profits in the corporate sector. Fluctuations in government revenues are related to market movement. Governments do not limit their expenditure to revenue they spend more normally.. Deficits arise when expenditure is more than revenue and surpluses result when revenue is more than expenditure. Government treasuries borrow on 31

the open market to finance short fall in revenue. These debts are repaid in periods of surpluses. Government may also print more currency notes but this causes inflation. It can be said in general that, stock market returns have positive relation with Fiscal surpluses and negative relation with Fiscal deficits.

2.4.4 Exchange rates An exchange rate is the ratio of how many units of one currency you can buy per unit of another currency. Unanticipated currency movements results in risk of changes in the value of assets and liabilities of a firm. It impacts on sales, prices and profits of importers and exporters. It also reduces competitiveness. Purely domestic firms which are not involved in imports and exports may also suffer from exchange rate risk when they compete with foreign companies in their home markets. The three main types of foreign exchange risk exposures are translation, transaction and operating exposure. There are three factors which cause the currency of a Country to appreciate or depreciate. These are: Differences in income growth: Nations with high income growth will demand more imported goods all other things being equal resulting in demand for more foreign currency leading to appreciation in foreign currencies relative to domestic currency. Differences in inflation rates: Consumers in a country with higher inflation rate will demand more imported (cheaper) goods from other Countries leading to appreciation of foreign currencies and depreciation of local currency. Differences in real interest rates: Differences in real interest rates results in a movement of capital from countries with lower real interest rates to countries with higher interest rates.

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2.4.5 Gross Domestic Product (GDP) Economic factors that impact on changing investment opportunities include macroeconomic factors which are measured by Gross Domestic Product (GDP), a measure of economic performance. GDP does not include purchase and sale of stocks since these are not production of goods. GDP measures both output and income. If output increases per person this translates into higher standard of living. GDP does not measure homemaker services and other non market production nor underground economy e.g. Illegal activities and tax evasion. Economic growth is the increase in value of goods and services

produced in an economy. It results from saving and use of capital, increase in work force and from technological changes. It is measured by the percentage increase in the real Gross Domestic Product (GDP). GDP is the total market value of all domestically produced final goods and services in a given year. It includes income earned by foreigners but excludes income earned by citizens abroad. The Expenditure approach is measured by the summation of the following. GDP = C + I + G + X, where (C) is household consumption of goods and services. ( I ) is expenditure of businesses. It includes capital replacement and new additions to capital assets, as well as investments in Inventory. (G) is Government consumption and gross investment. It includes purchases of goods and services by Government and its agencies. It excludes transfer payments. (X) is net export of goods and services.

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Current year values are used with a GDP deflator and base year values to derive real GDP. Factors that affect aggregate demand (GDP) in an economy include: Real Wealth: An increase in consumers real wealth will increase aggregate demand because of an increase in consumption. A fall in real wealth will lead to fall in consumption and for that matter GDP decreases. Real Interest Rates: An increase in real interest rates will lead to a decrease in consumer expenditure and business investment resulting in a decrease in aggregate demand. A decrease in real interest rate on the other hand increases aggregate demand through reduction in finance costs for both businesses and consumers. Inflation expectation: An expectation of future increase in inflation will increase aggregate demand whilst a decrease in the expected rate of inflation will reduce current purchases and aggregate demand. Exchange rate fluctuations: Currency appreciation leads to an increase in the value of the domestic currency (GH) compared to other currencies. This makes imports less expensive leading to an increase. Exports on the other hand become more expensive to foreign consumers leading to a fall. Since Ghana imports more than it exports on aggregate basis, Net Exports (Exports-Imports) will be negative leading to a fall in aggregate demand. Currency depreciation will on the other hand increase exports and reduce imports leading to increase in aggregate demand. Economic Expectations: Positive expectation about the future prospects of the economy increases aggregate demand resulting

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from increase business investment in capital in anticipation of increased future sales. Higher productivity from both capital and labour will increase aggregate demand. Investment in research and development as well as Innovations and technological development will increase aggregate demand. The rate of local capital accumulation also affects aggregate demand. Government policies in encouraging education, technological development, trade promotion, low taxes and high savings rates. An economy with increasing GDP all other things being equal will have rising Income. This will lead to an improvement in the disposable incomes of individuals. Demand for shares which is related to the level of disposable income will increase leading investors to buy more shares; the higher the demand for shares and higher the share prices to move up. When the economy is sluggish, the level of income and hence disposable income is affected negatively. There is no increase in production, employment is low leading to loss of jobs and reduced disposable income for most workers resulting in investors cutting back on their investments in shares. The resulting fall in demand for shares leads to a fall in share prices. 2.5 The Role Governments

Government can improve economic growth by adopting pragmatic policies that encourage growth by constantly monitoring the business cycle (contraction, recession, expansion and business peak). Governments can create an enabling environment by providing infrastructure (educational, technological, financial, physical, environmental, and social) as well as tax regimes and general confidence in the business environment.

35

Governments as agents of development and growth can also use their consumption and Investment to facilitate growth. Replacement, new and capacity enhancement investment in facilities that boost business production will provide good investment climate. Governments investment in infrastructure is a necessary tool in boosting business confidence.

Governments wishing to promote economic growth may endeavour to maintain incremental macroeconomic stability. They should avoid budget deficits and excessive surpluses. Time lags in recognition, implementation and impact of policy should also be monitored and controlled to ensure policy interventions yield desired results.

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3:0

Methodology

This section provides an overview of the data collection, variable selection, model specification and tests conducted. There exists no theoretical framework for selection of macroeconomic variables that affect stock market performance. Economic theory suggests that stock market prices should reflect expectation about future corporate cash flows which generally reflect the level of economic activities relate to aggregate output such as Industrial Production or GDP. If stock prices reflect the underlying fundamentals, then the stock prices could be used as indicators for future economic activities. It can be said therefore that the relationship between stock prices and macroeconomic variables are useful in formulation of macroeconomic policies. 3.1 Data Collection

Monthly time series data from January 1991 to December 2008 was used in the model. Data on Fiscal balance, Inflation, 91 day Treasury bill rates and Exchange rates movements were obtained from the Bank of Ghana. Stock Index movements were obtained from the Ghana Stock Exchange. The Ghana Stock Exchange, All Share Index (GSI) is a composite index which measures price movements of all equities listed on the exchange. The index is based on the low and high prices within the month/year as against beginning and closing figures. 3.2 Variable Selection

There is no economic theory that explains the linkage between macroeconomic factors and stock market performance but there are several macroeconomic factors that have been identified as having impact on stock prices. This study uses dividend discount model to select the variables considered in the study.

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Returns on stocks market are two fold. Capital Gains (price changes) and Dividend yield. Capital gains are the percentage increase or decrease in the price of an investment and includes gains or losses due to changes in exchange rates. Capital gains are computed by (P1/P0-1)*100. Dividend yield is stated as a percentage of price (D1/P0 )*100. Where P1 is current period prices and P0 is last period prices and D1 is current period dividend per share. This study considers only capital gains computed on the basis of high and low price movements in the month/year. Dividend yield is excluded because of lack of data. Changes in the earning capacity of a firm depend on general economic and market conditions. A change in individual stock returns depends on changes in rates of return for the entire stock market and the stocks Industry. This requires examination of Macroeconomic, Industry and Individual stock performance, but this study is limited to the impact of macroeconomic factors on the entire stock market irrespective industry differences. Gordons Dividend Growth model assumes constant growth. The value of a stock is derived from P0 = . D0(1+g) k-g or D1 k-g

where, g is constant growth in dividend, k is the required rate of return and D1 is expected dividend, which is a product of current dividend and growth rate. It is clear from the equation above that price depends on market discount rates and expected stream of dividend payments and growth factors. Expected inflation is built up in prices and projections so it may not affect stock prices, but unanticipated inflation may directly influence stock prices through changes in price level and through increases in discount rates. An increase in

38

discount rates reduces, the present value of corporate cash flows. The impact of inflation on discount rates and price levels makes it imperative for its inclusion in model. Money supply directly impact on interest rates. Interest rates influence investment decision on holding non interest bearing securities or interest bearing securities. At high interest rates, Investors may sell Equities to invest in Treasury Instruments. Interest rates change the discount rate in the valuation model and influences current and future cash flows. Long term bond yield will have been ideal for this studies, due to lack of data availability we use the 91 day treasury bills, which is more sensitive to the market at all times than the one year rate in an inverted term structure of interest rates which currently exists in Ghana. The Ghanaian economy depends largely on loans, donor support and remittances from citizens of Ghana resident abroad. The shares of AGC and Golden Resources are traded on foreign stock markets. Prices of houses, cars and other consumer items are quoted in dollars. Fluctuations in the dollar rate, which represent all foreign currencies, have significant impact on the economy therefore its inclusion in the model.

3.3

Model Specification

The GSI is the dependent variable of the regression equation. It represents the performance indicator of the Ghana Stock Exchange. Fiscal Deficits/Surpluses captures the income and expenditure position of the economy; Interest rates are approximated by 91 day Treasury bills; Inflation rate and Exchange rates are the other independent variables. The model is:

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GSI = 0 + 1FD + 2INTrate + 3INFrate + 4EXrate + 5GDP + et

Eq1

where GSI is the Ghana Stock Index, FD is Fiscal position, INTrate is interest rate, INFrate is inflation rate, EXrate is the exchange rate and GDP is gross domestic product, 0 - 5 are coefficients of variables and et is the error term, representing others factors not considered in the model e.g. Oil price hike and change in Government. To examine causal relationship of the variables we specify the following multivariate model: U = (GSI, GDP, Fiscal, Interest, Inflation, Exchange) where GSI is the Ghana Stock Index, GDP is gross domestic product. Fiscal is the fiscal position of Income and Expenditures, Interest is interest rate, Inflation is inflation rate, and Exchange is the exchange rate. 3.4 .0 Tests conducted 3.4.1 Visual Inspection: Visual inspection of the time series data was observed and comments made on movement in the variables. 3.4.2 Unit roots Tests Standard inference procedures do not apply when regressions contain integrated dependent variables or integrated regressors so it is necessary to ascertain whether a series is stationary or not before using regressors since the eventual results may be spurious. A series is stationery if the mean and auto-covariance are not time dependent. If the first differences are stationery, the series is said to

40

be integrated by the order 1(d) where d is the order of integration. The order of integration defines the number of unit roots contained in the series or the number of differentiations it takes to make the series stationary. Stationarity ensures that the variables are stationary and that shocks are temporary and will revert to long term mean after the effect of the shock. It is useful in deriving meaningful statistics such as means, variances and correlations. Unit roots tests was applied using Augmented Dickey Fuller (ADF) test with automatic maximum lag of 14 and Schwarz Information criterion to ascertain the order of integration of each variable to ensure stationarity of the variables. The automatic lag period 14 measures the correlation between observation 1 and 15, observation 2 and 16 in that order. The existence of unit root means the data set is non-stationary. Nonstationary time series data tend to be auto correlated whilst stationary time series data tend to be random. The ADF calculates a test statistics which if greater than the Dickey Fuller critical values, the null hypothesis can be rejected and conclusions drawn that the data had unit roots and so they are stationary. The critical values used for this study is -2.875 at 5%. We first test the original data. It was found to be non stationary so we make the data set stationary by taking the first difference transformation, in order to eliminate the trend relationships in the data. 3.4.3 Cointegration Tests To establish long term relationships and co-movement among the variables, Co integration techniques by Johansen and Juselius (1990), Johansen (1991) protocols was used instead of Engle and Granger (1987) because the analytical software EViews is limited to Johansen protocol. The Johansens (1991) Vector Error Correction Model also allows testing for cointegration in a whole series of equations in one step without requiring normalization of variables unlike the two step approach of Engel and Granger (1997).

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If two series are co integrated or have long term relationship, it means there exists a stationery linear combination of these series and the series are of the same order. A unit root test for stationarity of the time series data is first determined before the cointegration test. This test determines the existence of a unit root test of each series. The series are observed to determine whether they are stationary or they are integrated of the same order. If two variables are nonstationary but stationary in first difference, the series can be said to be integrated of order one. Thus they are I(1) series. Cointegration tests were performed using Johansen VECM using ordinary least square regression. There are two tests; the trace statistics which tests the null hypothesis that there are at most r cointegrating relationships and the eigenvalue statistic which tests the hypothesis of r cointegrating relationships against the defined alternative of r+1 cointegrating relationships. examined. 3.4.4 Vector Error Correction Cointegration was confirmed so Johansen and Juselius (1990) Error Correction Model was used to establish short run causal relationship between the two variables. Vector Error Correction model is a system of equations for which, each variable is a function of its own lag and the lag of other variables in the system. The variables have an order 1 and are cointegrated. The F tests of the explanatory variables determined indicate short run relationships. 3.4.5 Granger causality tests Granger causality tests using bivariate vector autoregressive method was used for all pairs of the series in the group. It measures the precedence and information content but does not by itself indicate causality in the more common An advantage of the cointegration analysis is that co-movement among the variables can be

42

use of the term. It examines short term causal relationships between the stock returns and each variable by calculating F statistic of the joint hypothesis. If one variable does not improve the forecasting ability of the other variable, then the first variable does not Granger cause the second. If the F statistic is significant, we can reject the null hypothesis that variable 1 does not Granger cause variable 2. 3.5 Data Description

The data covered a period of eighteen (18) years with two hundred and sixteen (216) observations on GSE, real GDP, FISCAL, INFLATION, INTEREST and percentage change in Exchange Rates. GES, real GDP, INFLATION and INTERST rates are expressed in percentages. Fiscal is the fiscal balance as a percentage of GDP Table below gives the summary of the data.Table 2. Summary of Data Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations GSE 43.75667 30.84500 154.6700 -15.22000 47.93129 0.870153 2.699739 28.06942 0.000001 9451.440 493942.8 216 GDP 4.883333 4.650000 7.300000 3.300000 0.994637 0.657757 2.952106 15.59582 0.000411 1054.800 212.7000 216 FISCAL -4.522222 -4.580000 2.260000 -11.48000 3.658188 0.200122 2.356296 5.170946 0.075360 -976.8000 2877.203 216 INFLATION 24.08683 18.11500 70.80000 0.390368 16.71154 1.466142 4.630702 101.3173 0.000000 5202.756 60044.22 216 INTEREST 28.22486 27.00000 47.93000 9.600000 12.01295 0.119472 1.922574 10.96147 0.004166 6096.570 31026.87 216 EXCHANGE -1.172062 -0.935779 0.181738 -3.365348 1.126772 -0.526171 1.876563 21.32581 0.000023 -253.1654 272.9673 216

The sample period recorded average fiscal deficit of 4.5% and exchange rates show an average percentage change of 1.17% change. The Ghana Stock Exchange shows a mean performance rate of 43%. All variables are positively skewed above normal with the exception of exchange which is negatively skewed. It indicated that there are outliers which are greater than the mean in all

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the variables with the exception of exchange which have outliers less than the mean. All the variables have relatively low Kurtosis. They are all more or less peaked than a normal distribution which has a Kurtosis of 3 standard deviations. GDP looks normal whilst GSE, Fiscal, Interest and Exchange are less peaked than normal distribution. Inflation is more peaked than normal distribution. Jarque- Bera statistics significantly rejects normal distribution of all the variables indicating non-normality. The coefficient of variation (Standard Deviation/Mean) as shown below is used to examine the volatility of each macroeconomic factor. GSE GDP FISCAL -0.81 INFLATION INTEREST 0.694 0.425 EXCHANGE -0.96

1.095 0.20

This shows that the Ghana Stock returns are very volatile, recording over 100%. Exchange rate, and Inflation and Fiscal fluctuations also show wide variability. GDP and Treasury bill rates are more stable than the other variables. 3.6 Regression

Table 3 RegressionDependent Variable: GSE Method: Least Squares Date: 11/23/09 Time: 10:13 Sample: 1991M01 2008M12 Included observations: 216 Variable GDP FISCAL INTEREST INFLATION EXCHANGE R-squared Adjusted R-squared S.E. of regression Sum squared resid Coefficient 6.408043 1.376725 -0.043016 0.992898 -2.081595 0.148491 0.132349 44.64693 420596.5 Std. Error 1.563947 0.868126 0.226801 0.199781 1.291448 t-Statistic 4.097352 1.585859 -0.189666 4.969923 -1.611831 Prob. 0.0001 0.1143 0.8498 0.0000 0.1085 43.75667 47.93129 10.45832 10.53646

Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion

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Log likelihood Durbin-Watson stat

-1124.499 0.134767

Hannan-Quinn criter.

10.48989

Table 3 shows the results of multiple regressions of all the variables. The results indicate that less than 15% of movement in the stock market is explained by the independent variables. This regression is not valid because the variables are cointegrated. Multiple regression analysis alone is not be able to answer the research questions since the variables of interest are interdependent and the analysis require a test of the stationarity of the data to establish the causality of price movement and dependencies of the variables. The original time series data was used to conduct an Ordinary Least Squares regression between two variables at a time under the model: Yt = a + Bxt + ut

Eq2

Where, ut is the estimated residuals on the long run equilibrium to establish the existence of unit roots.

3.7.0 Hypothesis The following hypotheses were made about the relationships between short and long term interest rates, inflation, exchange rates, fiscal balances and GDP. 3.7.1 Interest rates Dividend discount valuation model is very elaborate on the impact of interest rates on the price of stock. In Gordons constant dividend model,

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P =D1/ (k-g) ------------------------

equation 1,

Where P is the stock price, D1 is dividend after first year, g is the constant growth in dividend, and k is required rate of return. Changes in both short and long term interest rates affect discount rates used by investors to evaluate projects. From the equation above, if k is greater than g, there is a negative relationship between k and P. If k increases, P reduces. The first hypothesis is that: There is a negative relationship between interest rates and stock prices.

Intuitively, interest rates influence corporate profits, and therefore expected future dividend payments. The lower the interest rates the more profit available for reinvestment or for distribution, the more future expectation and the more willing investors are to buy the shares leading to increase in prices. Investors using borrowed funds will enjoy reduction in interest rates because of its impact on cost of borrowing. Reduction in interest rates will increase demand for shares since investors will require lower rate of returns to buy shares. High interest rates encourages investors to make quick money by buying treasury bills at the expense of stocks this results in reduced demand and eventually drive down prices. 3.7.2 Inflation The real rate of interest is the nominal rate minus inflation. Both short and long term inflation will directly result in higher real rates leading to higher discount rates. From equation 1, the hypothesis stands as above for interest rates that:

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There is a negative relationship between inflation and stock prices on condition that inflationary movements are unanticipated. High Inflation rates increase the cost of living and divert resources from investment on the stock market to consumables and real estate among others whose prices are on the increase in order to preserve capital. This results in low trading volumes and general lack of liquidity of the stock market. Lack of liquidity and low demand constrain traders to accept discounts on shares they offer for sale, this culminates in low prices. Inflation may lead to increase in cash flows but the increase can not buy the same basket of goods and services because cash flows will not grow at the same rate. An increase in Inflation directly increases the nominal risk free rate of interest which raises the discount rate resulting on negative impact on the price of shares and the general performance of the Stock Index. If inflation is expected however, all pricing in the economy will include inflation expectation, stock market prices are relatively well priced, so one will expect that inflation will have positive effect on the stock market returns.

3.7.3 Exchange Rates The Ghanaian economy is import dependent. Trade balances are mostly in deficit. Depreciation of the currency against the dollar in particular hurts the economy greatly, as cost of production goes up, corporate profits reduce. Depreciation of the cedi however favours exporters. Export oriented companies on the exchange will experienced increase economic activity with depreciation but since Ghana is import dependent, I hypothesis that:

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Depreciation of the Ghanaian currency has negative impact on the stock exchange and stock prices. 3.7.4 Fiscal Deficits/Surpluses

An increase in budged deficit requires more money to finance the deficit resulting in increased money supply or open market operation by the Central Bank. Increased interest rates which come with selling Treasury instruments stave listed companies of needed capital as returns on treasury instruments become very lucrative far above the short term returns of the stock market. I hypothesis that: There is a negative/ (positive) relationship between budget deficits/ (surpluses) and stock market returns. 3.7.5 Gross Domestic Product

Gross Domestic Product measures the real economic activities. It is high during periods of economic growth and low during periods of contraction. I hypothesis that; There is a positive relationship between GDP growth and stock market returns. 4.0 4.1 Data Analysis Unit Root Tests

It is necessary to ascertain whether a time series data is stationary or nonstationary before relying on regression analysis because there is a danger of

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obtaining regression results from unrelated data from nonstationary series yielding spurious regression. Unit Roots tests for stationarity were used to identify the order of integration. The results listed below shows that the calculated Augmented Dickey Fuller (ADF) test is greater than the test statistics so we do not reject the hull hypothesis of nonstationarity, thus all the variables are nonstationary. We however need to transform the series to stationary. The lag length used for the ADF test is based on Schwartz information Criterion (SIC). The indicative lag ranged from zero (0) to twelve (12).

Table 4: Summary of Level 1 ADF Unit Root Test *Variables GSE GDP FISCAL INTEREST INFLATION EXCHANGE Levels -2.705 0.265 -1.403 -1.619 -2.282 0.045 t-statistic -2.875 -2.875 -2.875 -2.875 -2.875 -2.875 Lag Length 0 12 0 1 1 3

* Calculated ADF is greater than 5% critical value so we do not reject the null hypothesis of non stationarity

The original series based on the ADF tests are non stationary so we take the first difference transformation of the non stationary data and based on ADF test. The series is now stationary because the calculated ADF is lower than the test statistic as shown in Table 5. We therefore reject the null hypothesis of nonstationarity.

Table 5: Summary of Level 2: ADF Unit Root Test **

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Variables GSE GDP FISCAL INFLATION INTEREST EXCHANGE

First Difference -14.595 -8.031 -14.594 -10.459 -12.595 -12.876

t-statistic -2.875 -2.875 -2.875 -2.875 -2.875 -2.875

Lag Length 0 11 0 0 0 2

** Calculated ADF is less than 5% critical value so we reject the null hypothesis of non stationarity.

This shows that an equilibrium relationship has been established to enable us deduce long run relationships. This implies two or more variables cannot move independently of each other and data from a linear combination of any two variables can be stationary despite the fact that those variables may be individually non stationary, this is however only possible if the variables are integrated to the same order (order 1) as the trends in both series cancel each other. 4.2 Cointegration

Methodology of Johansen (1991) was used to test the model to determine the rank, r and to find the cointegrating relationships in the model. Selection was made for intercept and no trend for the cointegrating equation. It was noted that the lag length was very relevant in the long term relationship of the variables, lag length of 2 to 6 for instance yielded no cointegrating equation but lag period of 10 to 15 showed one cointegrating equation for both Trace and Eigenvalue tests at 5% significance level, as indicated in Appendix B. The null hypothesis for the Trace test, is that the number of cointegrating vectors is less than or equal to 1 against an alternative hypothesis that there are more than 1 cointegrating vectors. The Maximal Eigenvalue test has the null

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hypothesis is that there are r cointegrating vectors present against the alternative that there are (r+1) present. The normalized cointegrating coefficients for the model is shown below Yt = (GSEt 1 = (1.00 GDPt, - 4.19 FISCALt + 3.12 INTERESTt + 2.14 INFLATIONt - 3.81 + EXCHANGEt) is 1.21)

The cointegrating relationship can be re expressed asGSE = 4.19 GDP - 3.12 FISCAL 2.14 INTEREST + 3.81 INFLATION 1.21 EXCHANGE

(3.8)

(7.2)

(2.9)

(1.8)

(9.0)

The coefficients are all significant and those of GDP and Inflation are positive whilst those of Fiscal, Interest and Exchange rates are negative. This indicates that GDP and Inflation are positively related to the GSE and negatively related to Fiscal, balances, Interest rates and Exchange. The existence of cointegration implies significant error correction term, which also is an indirect test of short run causality. The coefficients are significant. It indicates co-movement between stock market performance and the macroeconomic variables of interest in this study. It establishes long run equilibrium relationship.

The table 7 below shows the normalized co-integration equation and the adjustment coefficients. Table 7 Normalized Co-integration equation1 Cointegrating Equation(s): Log likelihood 2103.563

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Normalized cointegrating coefficients (standard error in parentheses) GSE GDP FISCAL INTEREST INFLATION 1.000000 -4.19E-16 3.12E-16 2.14E-16 -3.81E-18 (3.8E-08) (7.2E-09) (2.9E-09) (1.8E-09) Adjustment coefficients (standard error in parentheses) D(GSE) -1.000000 (1.6E-09) D(GDP) -0.002605 (0.00116) D(FISCAL) 0.003518 (0.00528) D(INTEREST) -0.002204 (0.01025) D(INFLATION) -0.037004 (0.02077) D(EXCHANGE) -3.82E-05 (0.00041)

EXCHANGE 1.21E-14 (9.0E-08)

The movement away from the long term equilibrium is determined by the adjusting coefficients. This shows insignificant movement with the exception of Exchange which responds quickly to short term shocks in the opposite direction. The coefficient of -1.2 compared with adjusting coefficient of 3.8, is possible to affect the long run equilibrium.

4.3

Vector Error Correction Analysis

Since the variables have an order 1 and are cointegrated, we proceed to examine the short run causal relationship between the Ghana Stock Index and the macroeconomic factors of interest, using the Vector Error Correction model, which is a system of equations for which each variable is a function of its own lag and the lag of other variables in the system. It is useful for identifying and testing the short run equilibrium relationship among the variables and to ascertain the impact of each macroeconomic variable on the stock market returns. The error correction term and their joint significance are provided by the F statistics. The F statistics listed in Appendix 3 range from 1.59 to 5.96. This rejects the null hypothesis that the coefficients of the variables are equal to zero. As shown in

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the error correction equation in table 9 below: all the variables contribute towards the error correction process. This indicated short term relationship. Table 8 Error Correction equationError Correction: CointEq1 D(GSE) -1.000000 (1.6E-09) [-6.2e+08] D(GDP) -0.002605 (0.00116) [-2.23989] D(FISCAL) 0.003518 (0.00528) [ 0.66682] D(INTEREST) D(INFLATION) D(EXCHANGE) -0.002204 (0.01025) [-0.21502] -0.037004 (0.02077) [-1.78167] -3.82E-05 (0.00041) [-0.09390]

The table above shows that Interest and Exchange have coefficients in opposite direction but all the other variables have error correction coefficients with the right sign. The speed of adjustment appears to be fastest for Exchange but it not statistically significant. The other variables are very slow this gives an indication that it takes a long time for stock market to get back to equilibrium after changes in macroeconomic variables. This result suggests less effective short term relationship between the Ghana Stock Market returns and the macroeconomic variables.

Table 9 Regression of Stationary DataD(GSE) D(GDP) D(FISCAL) D(INTEREST) D(INFLATION) D(EXCHANGE)

R-squared Adj. R-squared Sum sq. resides S.E. equation F-statistic Log likelihood Akaike AIC Schwarz SC Mean dependent S.D. dependent ,

1.000000 1.000000 5.90E-25 6.05E-14 4.34E+29

0.308450 17.43455

0.431654 0.297510 5.832479 0.190333 3.217848 69.69982 -0.306998 0.336174 0.017000 0.227088 1.07E-29 2.92E-30 2038.733 -17.98733 -14.02935

0.355578 0.203478 119.9482 0.863145 2.337793 -232.6620 2.716620 3.359792 -0.048500 0.967131

0.272909 0.101298 452.8057 1.677038 1.590273 -365.5023 4.045023 4.688195 -0.003650 1.769030

0.558877 0.454761 1859.414 3.398405 5.367835 -506.7576 5.457576 6.100748 -0.080350 4.602373

0.584641 0.486606 0.712664 0.066532 5.963584 279.9186 -2.409186 -1.766014 0.005793 0.092855

Determinant resid covariance (dof adj.) Determinant resid covariance Log likelihood Akaike information criterion Schwarz criterion

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Table 10 shows regression of stationary data. R2 show low to medium explanatory power of the variables considered. 4.4 Granger Causality

The existence of relationship between macroeconomic factors examined above does not help in determining the direction of causality. We select a lag length of fifteen (15) to conduct Granger causality tests to examine the causal relationships of each variable and the stock market returns using bivariate vector autoregressive model. explanatory variable. F test was used to test for the significance of each

From the table above, it can be concluded that: Fiscal Granger cause GSE and GSE granger cause Fiscal in a bivariate direction. Exchange Granger cause GSE but GSE does not Granger cause exchange. It is unilateral relationship. GDP Granger cause Exchange but Exchange does not Granger because Exchange It is a unilateral relationship Fiscal Granger cause inflation but Inflation does not Granger cause Fiscal. It is a unilateral relationship Exchange Granger cause Inflation and Inflation Granger cause Exchange, in a bivariate relationship. 5.0 Research Findings

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Results obtained from the analysis of data indicated that macroeconomic factors considered in this study have unit roots and so multiple regression analysis will not yield any meaningful results. Cointegration analysis shows that all the variables of interest have significant coefficients indicating long term relationship. The speed of correction in the short term is slow; this is confirmed by Granger causality test. The results indicate that the Ghana Stock exchange has a positive long run relations ship with GDP and Inflation but negative long term with fiscal, interest rates and exchange rates. These results are substantially in line with findings reported in earlier studies of the GSE. Anthony Kyereboah-Coleman (2008), Kwame Agire-Tettey (2008) and Frimpong (2009) reported that Treasury Bill rates (Interest) have negative impact on Ghana Stock Exchange returns. High interest rates will lead to diversion of investment funds from the exchange to money market. This study indicated that Inflation has a positive influence on the Ghana Stock Market returns. This confirms the findings of Anthony Kyereboah-Coleman (2008), but is contrary to the findings of Kwame Agire-Tettey (2008) and Frimpong (2009). This study also indicate exchange rates have negative influence on the market which confirms the findings of Anthony Kyereboah-Coleman (2008), but is contrary to the findings of Kwame Agire-Tettey (2008) and Frimpong (2009) as in the case of Inflation. The comparative results are shown in table 12. Table 12 Comparative results of studies on GSEMacroeconomic Factor

GDP FISCAL INTEREST INFLATION EXCHANGE

Coleman& Tettey N/A N/A +

Anokye & Tweneboah

N/A N/A + -

Frimpong N/A N/A +

This Study + + -

The differences in findings can be explained firstly by consideration of expectation theory and the lag period considered by the individual studies.

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Inflation expectation makes Companies build their expectation in their prices for both long run and short run this deviated from the theoretical expected position. This study confirms the fact that the Ghana Stock Exchange does not respond quickly to changes in macroeconomic factors. Anokye and Tweneboah (2008) reported that the Exchange responds less to real activity than to monetary shocks. From their studies, it took five (5) quarters or twenty (20) months for shocks in Treasury Bills rates to have an impact on the Stock market. The period range from five (5) quarters to twelve (12) quarters which is essentially medium to long run. The transmission mechanism of macroeconomic factors need further studies to understand why changes in macroeconomic factors take a long time to have an impact on the market. A weak currency increase the price of imported goods so Companies of a net importing Country like Ghana will suffer with currency depreciation. Findings suggest that the stock exchange and the cedi move in the opposite direction, appreciation in the cedi reduces stock market performance and depreciation of the cedi strengthens stock market performance. This analysis emphasis the importance of lag in the implementation of economic policy based on expectation of economic activity. The lags include recognition, implementation and impact. The impact lag is shorter for fiscal policy than monetary policy. Unanticipated changes have greater impact than anticipated policy changes. Maintaining fiscal discipline was and is still a major challenge for Governments of Ghana. Stability can be achieve through conscious effort towards: Stable monetary growth, managing money supply with the hope of maintaining prices; maintaining fiscal deficit/ (surplus) during recession/ (expansion) by establishing automatic stabilizers.

These findings differ from the hypothesized expectations only in the case of inflation. Expected inflation have a positive relation with the GSE but it was

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expected that unanticipated inflation will have negative impact on the exchange but results of this study contradict that expectation. The justification could be that the pricing mechanism is very effective in inflation forecasting. Depreciation of the currency have negative impact on the GSE All Share Index but the short run adjusting coefficient suggests that depreciation of the Ghana Cedi could have positive relation with the market.

6.0 1.

Conclusions This paper examined the long and short run relationships between five (5) macroeconomic variables and Ghana Stock Exchange All Share Index for the period of eighteen (18) years, from January 1991 to December 2008. The macroeconomic factors considered were Gross Domestic Product, Fiscal balance, Inflation, Interest Rates and Exchange rate.

2.

There is no economic theory that explains the linkage between macroeconomic variables and stock market performance in any one direction but there are several macroeconomic factors that have been identified as having an impact on stock prices. This study used dividend discount model to select the variables used in the study.

3

The existence of cointegration between the variables was tested by establishing the order of cointegration, using unit roots test and then by performing rank tests using Johansen procedure to establish long run relationships before error correction and granger causality test were used to establish short term relation ships.

4

The effects of macroeconomic factors on the performance of stock markets cannot be generalized in a set in hypothesis or theories that is applicable to all nations. There are country differences depending on the

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structure of the economy and the policy transmission mechanism. Stock returns are normally influences by both international and local conditions. 5 The results of cointegration indicated single cointegration vector between the GSI and the macroeconomic factors examined. The coefficients from the cointegration vector normalized on GSE provided evidence of long run relationship between the GSI and the economic variables considered. The results provided evidence that the Ghana Stock Exchange is positively related to GDP and Inflation, and negatively related to Interest rates, Fiscal movements and Exchange rate fluctuations. 6 Empirical evidence in this study support expected relationship between the performance of the GSI and the macroeconomic variables considered, with the exception of Inflation. This possibly reflects the fact that Inflation expectation is factored in the pricing mechanism of the economy so only unanticipated inflationary movement can have a negative impact on the Ghana Stock Market and the economy at large. This suggests that the Bank of Ghanas Inflation targeting regime may be working well. It is also possible that the use of nominal rates instead of real rates might have contributed to this result. Depreciation of the currency have negative impact on the GSE All Share Index but the short run adjusting coefficient suggests that depreciation of the Ghana Cedi could have positive relation with the Exchange. The pace of adjust