analysis of the impact of interest and inflations rates on the ghana stock market
TRANSCRIPT
ANALYSIS OF THE IMPACT OF INTEREST RATES AND INFLATION ON
STOCK PRICES OF THE GHANA STOCK EXCHANGE- AN EMPIRICAL
STUDY
A MASTER’S DISSERTATION
IN
MSc. BANKING, FINANCE AND RISK MANAGEMENT
BYWILLIAMS ANKONG
SUPERVISED BY
DR STEVEN WALTERS
APRIL, 2011
CERTIFICATION
This dissertation is submitted in part requirement for the Degree of MSc in Banking,
Finance and Risk Management at the Glasgow Caledonian University.
I declare that this dissertation is my own original work and has not been submitted
elsewhere in fulfilment of any requirement of this or any other award.
Signature………………………
Date………………………….
I
DEDICATION
This dissertation is firstly dedicated to the Almighty God. His mercies are truly new
every morning. The dedication will not be complete without me mentioning the name of
my lovely wife Shirley Ankong and my beautiful princess Stacey. They are so dear to
me.
II
ACKNOWLEDGMENT
I would like to express my deepest appreciation to my supervisor, Dr. Steven Walters,
whose guidance and advice made this dissertation a success. I really appreciate your time
and support. Thank you so much.
My special thanks also go to all friends and family members especially my big brother
Charles for his support and all those who in diverse ways have contributed in making this
piece of work a reality. May God richly bless you all.
III
TABLE OF CONTENTS
ABSTRACT........................................................................................................................1
INTRODUCTION..............................................................................................................2
Aims of the dissertation.......................................................................................................3
Research question................................................................................................................5
Dissertation structure...........................................................................................................5
CHAPTER ONE: THE GHANA STOCK MARKET.......................................................7
Introduction..........................................................................................................................7
Background ........................................................................................................................8
History and Development of the Ghana Stock Market.......................................................9
Ghana Stock Market Regulation and Supervision.............................................................11
Information Disclosure Requirement…………………….................................................12
Public Knowledge of the Securities Market......................................................................14
CHAPTER TWO: LITERATURE REVIEW....................................................................16
Introduction........................................................................................................................16
2.1 Effect of Interest Rate on Stock Price Movements......................................................17
2.1.1 Level and Movement of Interest Rates.....................................................................18
2.1.2 The Behaviour of Interest Rates in Sub-Saharan Africa………………….…………......19
2.1.3 Effects of Interest Rates on Stock Prices in Emerging Markets….............................22
2.1.4 Effects of Interest Rates on Stock Prices in Developed Markets.............................25
2.2 Effects of Inflation on Interest Rates...........................................................................27
2.3 The effect of Inflation on Stock Prices........................................................................28
IV
2.4 The effect of Inflation on Stock Returns……………..................................................30
2.5 The Efficient Market Hypothesis (EMH)....................................................................32
CHAPTER THREE: RESEARCH METHODOLOGY....................................................35
Introduction........................................................................................................................35
3.1 Research Approach.....................................................................................................36
3.1.1 Scientific Approach..................................................................................................36
3.1.2 Research Strategy………………………………………………………….………37
3.2Data...............................................................................................................................38
3.2.1 Data Description.......................................................................................................38
3.2.2 Collection of Data....................................................................................................39
3.3 Model Summary...........................................................................................................40
3.3.1 Model Specification..................................................................................................40
3.3.2 Model Justification...................................................................................................42
3.4 Analytical Tools..........................................................................................................43
3.4.1 Correlation Analysis.................................................................................................43
3.4.2 Multicollinearity.......................................................................................................44
3.5 Model and Data Criticism............................................................................................44
CHAPTER FOUR: DATA ANALYSIS AND PRESENTATION...................................46
4.1 Results..........................................................................................................................46
4.2 Correlation Test Results and Analysis.........................................................................47
4.3 Descriptive Statistics Results and Analysis.................................................................48
4.4 Regression with Multiple Factor................................................................................50
4.4.1 Effect of Interest Rate and Inflation on Share prices...............................................50
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4.4.2 Hypothesis testing and Analysis..............................................................................50
4.5 Single Factor Regression Analysis.............................................................................54
4.5.1 Regression Analysis of the effect of Interest Rate on Share Prices........................54
4.5.2 Regression Analysis of the effect of Inflation on Share Prices...............................56
4.5.3 Regression Analysis of the effect of Inflation on Interest Rate..............................59
CHAPTER FIVE: DISCUSSIONS AND CONCLUSION.............................................61
5.0 Discussions and Conclusion…………………………………….………….….….…61
5.1 Implications and Recommendation.............................................................................62
5.2 Limitation....................................................................................................................63
5.3 Reliability and Validity...............................................................................................63
5.5 Suggestion for further Research..................................................................................64
REFERENCES..................................................................................................................65
APPENDICES..................................................................................................................76
VI
LIST OF TABLES
Table 3.0: Summary of description and source of data…….……….…………………27
Table 4.0: Summarised results of the correlation test................................................... 53
Table 4.1: Summary of descriptive statistics of the sample.......................................... 54
Table 4.2: Regression results of stock prices, interest rates and inflation.................... 57
Table 4.3: Regression results for stock prices and interest rates................................... 62
Table 4.4: Regression results stock prices and inflation............................................... 65
Table 4.5: Regression of relationship between earnings and interest.............................68
VII
LIST OF FIGURES
Figure 4.1: GSE All-Share Index stock prices and interest rates movement .................. 54
Figure 4.2: GSE All-Share Index stock prices and inflation levels ................................. 58
Figure 4.3: Interest rates and the level of inflation movement …………........................ 67
VIII
ABSTRACT
The study basically seeks to empirically examine the role of interest rates and inflation in
the movement of stock prices in Ghana from 1995 to 2009. The GSE All-Share Index is
used to represent the Ghana Stock Market whereas the Consumer Price Index and 91 days
Treasury bill rates are proxied for inflation and interest rates respectively. Considering
the fact that the Ghanaian economy is characterised by high interest rates as well as high
inflation pressures, it is important for investors to know whether stock prices in Ghana
are impacted heavily by inflation or interest rates. However, the results of the empirical
tests conducted revealed that the GSE All-Share Index is driven by interest rates but not
inflation as initially anticipated.
1
INTRODUCTION
The relationship that exists between macroeconomic variables and the development of
stock markets has been the subject of discussion over the past decade both in the
literature of practitioners’ and academia. According to Shiller (1988), changes in stock
prices reflect changes in investor’s expectations about future values of certain
macroeconomic variables that directly affect the pricing of equities. Fundamentally, some
macroeconomic variables such as exchange rate, interest rate, and inflation are believed
to determine stock prices (Glen, 1995). It is also largely expected that government fiscal
policy and other macroeconomic events have a significant effect on general economic
activities in an economy including the stock market. This has therefore become a source
of motivation for many researchers to study the dynamic relationship between stock
prices and macroeconomic variables. More significantly, preliminary studies have been
done using different approaches to investigate such links between stock prices and
macroeconomic variables. A more typical example of this is the study by Chen et al.
(1986), who used the Arbitrage Pricing Theory which is developed by Ross (1976) to
establish how macroeconomic variables explain movements in the US stock market. In a
related study, researchers such as Cheung and Ng (1998), McMillan and Humpe ( 1997),
Mukherjee and Naka (1995), Kwon and Shin (1999) and Mayasmai and Koh (2001) did
employ cointegration analysis to explain the link between earnings and macroeconomic
variables in developed countries like Japan, US, Australia, Canada and other European
countries.
Yet, it has been extremely difficult for some researchers to identify whether changes in
stock prices may be attributed to either nominal interest rate changes or inflation
2
movements or both. It is therefore worthy to undertake an empirical study that examines
whether certain macroeconomic fundamentals are capable of driving the behaviour of
financial aggregates.
The purpose of this study is to make contributions to the existing literature by examining
whether it is interest rates or inflation or both that are responsible for the movement of
stock prices in an economy with high inflation pressures such as the Ghanaian economy.
While previous studies have analysed the relationship between macroeconomic factors
and stock return volatility, no such study has been limited to stock prices, inflation and
interest rates. To attribute an increase or a decrease in stock prices to either inflation or
interest rates or both is without doubt very crucial for investors in the Ghana Stock
Exchange (GSE) due to the divergent views that have been put forward to examine the
relationship between stock prices, inflation and interest rates as well as other
macroeconomic variables.
Aims of the dissertation
The core objective of this Dissertation is to empirically determine the impact of interest
rate and inflation on stock prices of the Ghana Stock Exchange All-share Index from
1995 to 2009. The GSE All-share Index is the main stock index computed on the Ghana
Stock Exchange even though the Databank Stock Index (DSI) is the first ever stock index
computed by the Databank Group on the GSE. Besides being the main stock index, its
choice of selection is also motivated by data availability.
“Investing in stocks without doing the important stock market research first would be like throwing your money away on lottery tickets with the hope that you might get lucky” (Bionomicfuel.com, 2010)
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Any research into a stock market is deemed very important to investors, analyst, and
portfolio managers who normally rely on the outcomes to identify and to pursue their
investment objectives and opportunities. In their analysis of the economy as a whole,
Ologunde et al. (2006) posit that the stock market makes it possible for the economy to
ensure long-term commitments in real capital. As such, the level of efficiency
measurement of the stock market is very important to investors, policy makers and other
major players, who ensure long-term real capital in an economy. Clearly a mature stock
market efficiency level is perceived across the globe as a barometer of the economic
health and the prospect of a country as well as a register of the confidence of domestic
ddand global investors. It is worth noting that such ventures offer countless opportunities
for determining the future behaviour of stock prices as well as reducing probability of
high losses in the market (Chuppe, 1992). Undoubtedly, management of corporate
institutions will find the results of this research useful in determining how the firms’
performance translates into value for their current and prospective investors. Moreover,
regulators in the stock market can use the findings as bases for improving transactions on
stock exchanges. Finally, the usefulness of such an endeavour to corporate and
institutional management as well as governments cannot be overemphasised since the
variation in price among common stocks is of considerable interest for the discovery of
profitable investment opportunities, for the guidance of corporate financial policy, and
for the understanding of the psychology of investment behaviour.
This research begins by providing a brief overview of stock price movements and the
important factors affecting the stock price variations especially macroeconomic variables.
4
The second part of the study will identify and discus the relationship between stock prices
and the level of interest rates and inflation. The final part of this work is therefore
intended to discuss the implication of this relationship in investment decisions. Most
significantly, to determine whether investment decisions can be based on interest rates
levels as well as inflation or both.
The research question
The main research question that this study intends to address is:
Do interest rates and the level of inflation of the Ghanaian economy have any significant
impact on stock prices of the GSE All-share Index?
In answering the above question, an attempt will be made to addressing the following
questions:
Is there any significant relationship between interest rates, inflation and stock prices?
Is there any significant relationship between the level of interest rates and the level of
stock prices?
Is there any significant relationship between the level of inflation and the level of
stock prices?
Is there any significant relationship between interest rates and the level of inflation?
Dissertation structure
The dissertation is structured into five different chapters as already outlined above:
The concentration of chapter one is on the Ghanaian Stock Market. The main indices on
the Ghana Stock Exchange comprise the GSE All Share index and the Databank stock
5
index (DSI). According to Adam and Tweneboah (2008), three other new indices
comprising the SAS index (SASI), SAS Manufacturing index (SAS-MI) and the SAS
Financial index (SAS-FI) have also been published by Strategic African Securities
Limited. However, this study will be based on the GSE All-share Index. Primarily, the
discussions will be centered on the background, development, and current structure of the
GSE. Since the purpose of this study is intended to assess the impact of interest rates and
the level of inflation on stock price movements on the GSE All-share Index, the
background, function, and regulation of the underlying Ghana stock market, most
especially that of the All-share Index is deemed a necessary step to addressing the
research questions posed above. Certainly, the first part of this chapter looks at how
interest rates are determined by the Central bank of Ghana and how it can be influenced
by the level of inflation and their impact on stock prices. In addition to this, a review of
the relevant literature will be done on the extensive work covered by other researchers in
Chapter two. Chapter three is expected to cover the methodology and data, model
description, justification, and analytical tools selected for this study. Chapter four will
however dwell on interpretation, presentation and analysis of results whereas. Chapter
five provides a conclusion, limitations, and recommendation of the dissertation.
6
CHAPTER ONETHE STOCK MARKET OF GHANA
1.0 Introduction
Good investors always look to investing in an efficient market (Ologunde et al, 2006).
The prevalence of stock markets around the globe therefore comes as no surprise
particularly with the word ‘investment’ having become a household name in virtually
every part of the world. There is no doubt (Yucel and Kurt, 2003) how history has shown
that stocks have facilitated the expansion of companies. Clearly, the great potential of the
recently founded stock markets have become increasingly apparent to both the investors
and the companies alike. The devastative effect brought on the world’s economies by the
great crash of the stock market in1929 is a clear indication of the importance of its role in
the development of human race (Taylor and Tongs, 1989). Arguably, (Frank and Young,
1972) the most notable and the oldest exchanges can be found in London (The London
Stock Exchange), New York (The New York Stock Exchange) and in Mumbai (The
Bombay Stock Exchange). Again, stock exchanges such as the Osaka Stock Exchange in
Japan, the Singapore Exchange (SGX) in Singapore, the Frankfurt Stock Exchange in
Germany, the Hong Kong Stock Exchange etc have also succeeded in carving a niche for
themselves. However, the Ghana Stock Exchange though relatively young has been
recognised to compete with the big guns not only in the developing world but with the
developed as well. It therefore came not as a surprise when the Ghana Stock Market was
voted in 1993 and 1994 as the sixth and best performing emerging market respectively.
Certainly, the Ghana stock market has evolved over the years, with interesting story to
tell. This section provides a brief background to the formation of Ghana Stock Exchange
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in general, and its development of the GSE All-Share Index in particular. This is then
followed by an analysis of how trading activities are being regulated by the stock
exchange. Finally, a critical look at the main functions of the stock exchange will be
fundamental to the study.
1.2 The Background of Stock Markets
Arguably, stock markets have always been at the forefront in every facet of the world’s
economy whether booms or recessions alike. It is for this reason that newspapers and
financial publications have always had in their headlines information about the Dow
Jones, FTSE 100, NASDAQ, rising stock indexes, falling stock indexes, buying and
selling (Levine, 1990). It is therefore tempting (Dailami, 1992) to think of a stock market
as an impersonal mechanism somewhere in the sky, and imposing its mandates on us at
will. However, this is not usually the case. In reading the history of stock markets, it is
common for one to come across the words of the famous economist Thomas Sowell that:
“markets are as personal as the people in them” (Sowell, 1987). What this means is that,
stock markets and their performance reflect the dominant concerns, fears, and hopes of
the investing public. Contrary to the divergent views which have been expressed, stock
markets did not begin as the super-sophisticated, simultaneous and worldwide trading
exchanges as we see today. It is believed that the first institution that assumed the
responsibility of a stock market did not emerge until 1531, in Antwerp, Belgium. Hence,
as has been noted (Popiel, 1988:67), this was, “…the first stock market, sans stock.”
Because the buying and selling of corporate shares had by then not began, brokers and
lenders always gathered there to deal in business, government as well as even individual
8
debt issues (Popiel, 1988). The turn of events came not until the 1600′s, when Britain,
France, and the Netherlands had chartered voyages to the East Indies. It is believed
(Imperial Gazetteer, 1931) that on realizing that the few explorers could not afford to
conduct an overseas trade voyage, limited liability companies were set up to raise money
from investors, who received a share of profits commensurate with their investment. As
was famously reported (Imperial Gazetteer, 1931) in India, the earliest British voyages to
the Indian Ocean were unsuccessful and this resulted in lost ships. Accordingly, the
financier’s personal belongings were seized by creditors. This brought a group of London
merchants together to form a corporation in September of 1599 with the intention to limit
each member’s liability to any amount they personally invested. Certainly, in case the
voyage failed, nothing more than the stated amount could lawfully be seized. This
development therefore led to the Queen granting the merchants a fifteen year charter in
1600, referring to it as “The East India Company.” The newly adopted approach as it is
believed proved successful, leading to the subsequent grant of charters by King James I
to more trading companies by 1609 which triggered business growth in other ocean-
bordering European countries (Imperial Gazetteer, 1931).
Thus the Dutch East India Company was actually recognized as the first to allow outside
investors to purchase shares entitling them to a fixed percentage of the company’s profits.
In addition to that, they were also the first company to issue stocks and bonds to the
general public, through the Amsterdam Stock Exchange in 1602 according to Popiel
(1988). Figure 1.0 in the appendix A however shows the role of the investor,
intermediary and businesses or governments. As depicted in the appendix (figure 1.0),
stock exchanges as financial markets, provide the platform for household consumers who
9
want to save for future expenditure and for firms to raise capital for different investment
purposes (Benita and Lauterbach, 2004).
1.3 History and Development of the Ghana Stock Exchange
The idea of establishing a stock exchange in Ghana was hatched way back in 1968. This
initiative as it is believed led to the promulgation of the Stock Market Act of 1971, which
laid the foundation for the establishment of the Accra Stock Market Limited (ASML) in
1971. Lack of support from the then government, coupled with unfavourable
macroeconomic environment as well as the unstable nature of the political environment
were seen among the few obstacles that undermined the smooth take off of Accra Stock
Market Limited. The problems which have just been enumerated above meant that the
initial idea remained a mirage. Notwithstanding these obvious challenges at the initial
stages, an over the counter trading in foreign-owned corporate shares were carried out by
two prominent brokerage firms prior to November 1990 when the Ghana Stock
Exchange was established. These were National Trust Holding Company Ltd (NTHC)
and National Stockbrokers Ltd, now known as Merban Stockbrokers. In an effort to
recover from its economic woes, Ghana with the help of the IMF and World Bank had to
undergo structural reforms in 1983 to remove distortions in the economy. It is noted that
these financial reforms included but not limited to deregulation of interest rates, credit
control removals, and floating of exchange rates. Clearly it had become necessary for
Ghana to have a stock market after the financial liberalization and the divestiture of a
number of state owned enterprises. The Ghana Stock Exchange was finally incorporated
as a private company under the Ghana companies’ code, 1963(Act179) in July 1989.
10
However, in 1994, the status of the company had to be changed to a public company
under the company’s Code. The Ghana Stock Market as it is believed was finally
recognised as an authorized stock exchange under the stock Exchange Act of
1971.Trading activities began on the floor of the exchange on November 12, 1990.
Although the exchange interestingly began trading with only 13 listed companies, in
1991, the number had increased to 19 in 1995. The number of listed companies had
however astronomically risen to 32 in 2007(GSE Quarterly Report, 2007). The surge in
the number of listed companies has also had an enormous impact on market
capitalization. The Ghana stock market though relatively young has chucked remarkable
successes. The exchange was voted the sixth and the best performing emerging market in
1993 and 1994 respectively. The two main indices on the exchange are the Databank
Index and the GSE All-share Index. The GSE capital appreciated by 116% in 1993 and
gained 124.3% in its index level in 1994 (GSE quarterly bulletin, 1995). However, high
levels of inflation and interest rate accounted for its poor performance in 1995 in which
the growth in index was only 6.3%. The exchanges market capitalization at the end of
2004, stood at US$ 2,644 million. Meanwhile, the yearly turnover ratio just fell from an
all-time high of 6.5% in 1998 to 3.2% in 2004. An even more remarkable feat was
achieved by the exchange in October 2006 with a market capitalization of $11.5billion.
The Ghana Stock Exchange conducts trading every working day and all trading activities
are expected to be carried out on the floor of exchange except Ashanti Gold shares which
can both be traded through the GSE and over-the-counter after GSE trading hours though
all such trades must be subsequently reported to the GSE at the next trading session.
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1.3.1 The Ghana Stock Market Regulation and Supervision
The call for protection and security by investors in the capital market has been on the
ascendency in recent years due to the volatility of capital markets. It is expected that
capital markets most especially the emerging ones should operate within a framework of
rules and regulations enacted in order to make sure that there is order and fair play in the
dealings of securities. Clearly, the development of stock markets depends on the extent to
which these laws are enforced by the various regulatory agencies in any country. In
Ghana for instance, various laws have been made especially for the protection of the
securities’ market. These include the Securities Industry Law (SIL) 1993 (PNDCL 333).
The main purpose of this law is to spell out the establishment of the Securities Regulatory
Commission and the manner in which the commission should function. Basically, there
are two provisions for regulating firm’s dealings on the exchange as well as its
membership. These provisions are the Ghana Stock Exchange Listing Regulation 1990 LI
1509 and the Ghana Stock Exchange Membership Regulations 1990 LI 1510.
Meanwhile, in addition to maintaining the surveillance over the securities market, the
Securities Regulatory Commission (SRC) also functions to ensure order and equitable
dealings in securities. The SRC therefore has the power to license stock markets, unit
trusts, mutual funds, and securities dealers and investment advisers as well. This body is
also given the mandate to ensure the protection of the securities market against unlawful
practices like insider trading. In view of this, takeovers, mergers and acquisition of
companies are subject to the proper scrutiny, approval and regulation of the commission.
Mention could also be made of the Companies Code of 1963 (Act 179), the Bank of
Ghana Act, 1963 (Act 182), the Banking Law of 1989 (PNDCL 225) and the Financial
12
Institutions (Non-Banking) Law, 1993 PNDCL 328 as the other laws that govern the
securities market directly or indirectly. Certainly, the existence the of varied rules and
regulations in the Ghanaian market is an indication of the fact that the legal and
regulatory framework of the securities market as well as that of the stock market are
adequately taken care of compared to those of even more advanced nations. The question
regarding any evidence of legal enforcement in the stock market was perfectly answered
when three notable brokerage firms namely the Databank Brokerage Limited, EBG Stock
Brokers and SDC Brokerage Ltd. were suspended and fines imposed on them, in early
December 1995 for going contrary to the rules governing the operations of the financial
market. While Databank Ltd was only suspended from dealing on the floor of the stock
market for a number of trading days, the memberships of EBG Stock Brokers and SDC
Brokerage, Ltd. in the council of the Ghana Stock Market were terminated.
1.3.2 Information Disclosure Requirement
The disclosure of very important and relevant information about securities to the public is
not only crucial for pricing efficiency but for market confidence as well. It is worth
noting that investors can only make sound judgements about the value of securities only
when they are fully informed of relevant facts on the ground. Therefore, against this
background, there is the need to ensure that the disclosure policies governing listed
companies on the Ghana Stock Exchange, as stipulated in the Legislative Instrument (LI)
1509, is quite understandable. Interestingly, various regulations under this legislative
instrument have been clear on information that should be disclosed to the general public.
Regulation 55 for instance requires every company that is listed to make available to the
public every information necessary for informed decisions. Additionally, all listed firms
13
must take reasonable steps to ensure that all investors in the company's securities have
equal access to such information. On the other hand, regulation 56 requires a listed firm
to make immediate public disclosure of any information that is material concerning its
dealings. Listed firms are also required by law to release vital information to the public in
a manner designed to achieve its intended purpose of full disclosure. Regulation 57
however contends that if companies listed become aware of a rumour or report, which
may be true or otherwise, and that the information is likely to have or has had effect on
the trading of the company's securities or might have a bearing on investment decisions,
then the firm is required to publicly clarify the rumour or report as soon as possible. The
disclosure of information on financial reports is also well covered in Regulations 43 and
44. While Regulation 43 binds companies listed to give to the exchange a half-yearly
report immediately the figures are available and in any event not later than six months
after the end of the first half-yearly period in the financial year, Regulation 44, requires
listed companies to give to the exchange a preliminary annual financial statement
immediately the figures are made available and in any event not later than three months
after the end of the financial year. Among the information that should be disclosed in
both half-year and annual financial statements include turnover, consolidated operating
profit/loss, income from associated companies, extraordinary items, minority interests,
operating profit as percentage of turnover, operating profit as percentage of issued capital
and reserves at end of year, earnings in cedis per ordinary share and dividends, as well as
any amount payable per share and the date payable. More so, if a firm wants to be listed
on the exchange, the disclosure requirements demand that the company provides any
information about its background especially its history, line of business, capitalization,
14
the distribution of shares such as authorized and issued capital, and the distribution of
shareholders. It is also expected that other relevant information such as dividend records,
fiscal year end, date of annual meetings and any pending legal actions be disclosed.
1.3.3 Public Knowledge of the Securities Markets
Unlike the developed world, lack of knowledge and unfamiliarity with negotiable
instruments in emerging markets is very high and this is obviously expected to be a
significant constraint to the development of the securities markets in the developing
world. Ghana is thus not an exception to this scenario. However, many steps were taken
in the case of Ghana to ensure that this trend did not continue into the future. Various
short term courses have been organised by the GSE and are being run on a continuous
basis throughout the year to help educate all participants about securities. In all, five of
such courses are designed to meet the needs of both professionals and non-professionals
on various aspects of the securities industry on monthly basis. These include courses such
as Basic Securities, Advanced Securities, Securities Selling and Investment Advice,
Securities Trading, and Directors Course. The basic securities course is targeted at those
who are interested in knowing about the securities market in Ghana. Basically, the
advanced securities course is a foundation course for professionals in the securities
market place, as well as others in law, banking, accounting, insurance, finance and
economics, who require an in-depth understanding of the securities markets, instruments,
trading, legal issues and analysis of financial statements. The securities selling and
investment advice course is specifically designed for those individuals who are seeking
licensing as sales representatives and investment advisors. The securities trading course is
15
also a specified course for professionals who want to have an in-depth knowledge of
trading on the stock exchange as well as those who intend to seek licensing as authorized
dealers of stockholding firms. Rather strangely, the directors' course, though rarely
organised, is considered the most important course designed especially for directors of
stock broking firms. The course covers the roles and responsibilities of stock broking
firms in accordance with the regulations and laws of the securities industry and the Ghana
Stock Exchange. Once again it must be emphasised here that the efforts of the GSE in
this area are commendable. This therefore explains why, 1,682 people have been taken
through the five courses over the four-year period from 1991 to 1994. Nonetheless it is
interesting to note that this effort has not been emulated by other African stock
exchanges, such as the Lagos, Nairobi, Harare exchanges etc. Apparently, the effort of
the GSE is unique and hence it is expected to help foster growth and development of the
Ghana stock market. In spite of the remarkable successes that have been chucked, many
are of the view that the goal is far from being reached especially looking at the level of
knowledge of the total population. There is therefore the need for other institutions, such
as the universities, banks, brokerage houses, etc. to augment the effort of the GSE
through similar training programmes. The belief is that only through such collective
effort can pave the way for educational programmes to make a positive impact.
16
CHAPTER TWO
LITERATURE REVIEW
2.0 Introduction
Numerous writers have over the years conducted extensive empirical study regarding the
effect of several macroeconomic variables on the performance of stock markets, focusing
on investors' perspectives by looking at stock prices and returns. Yet, very little attention
has been paid to real interest rates and inflation especially in emerging markets like that
of Ghana even though these factors are considered very important. Moreover, there are
other important issues regarding the extent to which real interest rates and inflation may
impact on the sound performance of stock markets, in terms of the degree of trade, capital
issues and the dominance of major companies. There is therefore no doubt that such
issues need to be investigated. The view (Pill, 1997) has also been expressed in particular
regarding how crucial the results of such study can be especially in terms of success in
economic reform in emerging markets. An emerging stock market can thus be seen as an
important vehicle in a country's strategy to facilitate the flow of investment into the
business environment in order to accelerate economic growth and reduce external debt
(Ploeg, 1996).
The focus of this chapter is to provide a critical review of the related literature on the
subject under discussion. In doing this, a critical assessment of the strengths and
weaknesses of past studies focusing on stock price movements will be considered. The
first part of this investigation will center on the impact of interest rates on the movement
of stock price. The second part also explores the effect of the level of inflation on stock
17
prices. The third part looks at the relationship between interest rates and inflation and
how this (relationship) together with company fundamentals can affect stock price
movements in Ghana. The final analysis will be based on some stock pricing models with
the emphasis on efficient market hypothesis.
2.1 The effect of interest rates on stock price movements.
The importance of interest rates to businesses and the stock market in macroeconomic
theory cannot be overemphasized. In financial theory, it is stated that interest rates,
though has been changing frequently is fundamental to the valuation of a company and as
such plays an important role with regards to how we put a price on stocks. Yet, it is not
uncommon to hear that anyone who is ever looking for a topic to kill a conversation in
order to be left alone to think about his/her investment should consider talking about
interest rates (McClure, 2011). Simply put, an interest rate is essentially nothing but the
cost an individual or a person has to pay for the use of another person’s money.
Homeowners for instance pay interest on the money they borrow to purchase a home and
are therefore very familiar with this term. Another class of people who are also very
intimate with this scenario are credit card users. These people borrow money for the short
term to finance their purchases and in return pay interest for the privileges enjoyed.
However, the term interest rate means a different thing all together when it comes to the
stock market. In the US for instance, what concerns investors is the Federal Reserve’s
federal funds rate as this is the cost that US banks are charged for borrowing money from
the Federal Reserve banks. In other countries, this rate is determined by their respective
central banks (Saunders and Cornett, 2008).
18
Quite recently, the number of academic studies concerning the relationship between
interest rate and stock prices has been phenomenal. Many researchers have undertaken
empirical tests in considering the effect of interest rates on share prices. However, a
survey of the available literature reveals divergent views of the researchers on the issue of
the link between the two variables. Before delving deep into some of these views, a
cursory look at the factors affecting interest rates is deemed very remarkable for this
study.
2.1.1 The level of Interest rate Movements
The change in interest rate impacts on economic decisions, such as whether to save or
consume and given the effect of changes in interest rates on the value of firms, much
effort is being made to discover the factors responsible for this change (Jones et al.,
1993). Primarily, the government of any nation has a say in the behaviour of interest
rates. In most instances the monetary policy committee within the central banks of the
respective countries are given the responsibility to determine the level of interest rates
(Saunders and Cornett, 2008). But the central bank in the United States is called the
Federal Reserve (the Fed) which often comes out periodically to announce how the
monetary policy will influence interest. This activity is carried out by the seven member
board of governors as well as the five presidents of the Federal Reserve Bank through the
use of open market transactions (Jones et al., 1993). This as he explained basically
involves buying securities such as treasury bonds and bills which are already in
circulation or selling new ones. In effect, the activity of the board depends on what it
aims to achieve. Thus whenever the government wants to slow down growth in the
economy, it sells securities to banks and the general public in order to drain the system of
19
liquidity. This arguably renders banks with less disposable funds for lending. On the
other hand, the Fed (government) can also stimulate the economy through the purchase of
more securities thereby injecting more money into banks for lending purposes. For
example (Cornett and Saunders, 2008), the Fed had to lower interest rates aggressively in
2001 when the US economy showed signs of weakness. Interestingly, the Fed continued
to keep interest rates down even at a time when the economy had began to recover citing
inflation as a lesser concern than deflation. This therefore brings about the issue of the
relationship between interest rates and inflation regarding interest rate movement which
will be discussed later under this very chapter.
Apart from the activities of central banks which have been recognised as the main
culprits as far as changes in interest rate is concerned the forces of demand and supply do
also have a part to play in determining movements in the level of interest rates (Saunders
and Cornett, 2008). It is noted that the level of interest rates is a factor of the supply and
demand, hence an increase in the demand for credit (loanable funds) will lead to a
correspondent increase in interest rates and vice versa. In converse, an increase in the
supply of credit will reduce interest rate while a decrease in the supply of credit will bring
about interest rates increases (Jones et al., 1993). In his explanation, he intimated that the
supply of credit is increased by an increase in the amount of money available to
borrowers. He stated for example that money is always lent to a bank whenever a new
account is opened. The bank can therefore lend out any excess money. The more banks
can lend, the more credit there is in the economy. Consequently, as the supply of credit
increases, the cost of borrowing (interest rate) decreases and vice versa.
20
2.1.2 The Behaviour of Interest Rates in Sub-Saharan Africa (SSA)
Liberalization of interest rates has been one of the main policy goals of structural
adjustment in SSA. According to Agenor and Montiel (1996:152) interest rate ceilings
bring about a “wedge between the social and private rates of return on asset
accumulation, thereby distorting intertemporal choices in the economy”. Villanueva
(1988) also stresses the importance of interest rate reforms by pointing to the implications
these interest rate reforms have on monetary control and mobilization of savings. Interest
rate liberalizing simply involves an abolition or reduction of controls on both lending and
deposit rates. (Villanueva, 1988).
It is believed that two opposing effects on the relation between savings and interest rates
can be concluded. Firstly, it is expected that an increase in real interest rates will cause
consumers to defer present consumption and increase savings. Again, there is bound to be
an increase in income as a result of the increase in interest rates. Undoubtedly, this
increase in income increases demand as well as consumption. Dornbush and Reynoso
(1989) thus argue that the net effect of increased interest rates on savings is not very
clear. However, they noted that switching from negative to positive interest rates can
have a very important impact on financial savings. Accordingly, the effect stems from the
fact that with negative interest rates, potential savers may choose to save in more tangible
assets or export capital elsewhere in abroad. Meanwhile, it has been strongly contended
(World Bank, 1994) that the rationale behind interest rate liberalization in SSA is to align
interest rates toward market equilibrium in order to implicitly encourage savings but
Dornbush and Reynoso (1989) recognises the lack of empirical evidence of a strong
relationship between the rate of interest and the supply of savings. In spite of this,
21
McKinnon (1973) emphasises the need for high equilibrium interest rates contrary to the
Keynesian view that low interest rates promote investments as well as growth. In effect,
his (McKinnon, 1973) view suggests that any interest rate ceiling stifles savings and
increases current consumption as well.
Glower (1994) observes that liberalization is likely to lead to an in interest rate variability
which will be higher than what should be expected in the post reform level of interest
rate. Without a doubt, the experiences of SSA point to the fact that low positive real
interest rates have not been achieved after liberalization. As stated by Montiel (1995, 75),
“countries have tended either to continue to have negative interest rates or high positive
rates.” In confirming this statement, the World Bank (1994) notes that Cote d'lvoire and
Senegal had kept high positive interest rates for deposits for the period 1990-91.
Interestingly, countries like Ghana, Kenya and Uganda around the same period were
recognised as being in the ‘acceptable range’ whiles Zimbabwe was classed in the ‘highly
negative’ category.
These double standards prompted Stiglitz and Weiss (1981) to advance arguments against
high interest rates. In their argument, the writers emphasised that any attempt to charge
higher interest rates adversely impacts on a bank’s loan quality due to the incentive and
adverse selection effects. According to them, it increases the overall riskiness of the
portfolio of assets while reducing the returns on all projects and as such it makes less
risky projects less profitable. The effect of this therefore is that firms will be motivated to
switch to more risky projects in an environment of rising interest rates.
The other instance they posit is that, banks will have no choice than to screen borrowers.
However, if the screening device used is interest rate, they are most likely to take on very
22
risky borrowers. The reason behind this argument is that high interest borrowers may be
less worried about the prospect of nonpayment. Though one would expect banks to
monitor the behaviour of borrowers, information is deemed not only expensive but
imperfect as well. What this brings to mind is that the rational profit maximizing bank
will definitely practice credit rationing which eventually defeats the general assumption
made in financial liberalization literature, about the ability of interest rate liberalization to
eliminating credit rationing.
Not long ago, a research conducted by Nissanke (1990) on a number of SSA countries
revealed that interest rate deregulations have had little or no impact on savings and for
that matter stock price. Similarly, Choo and Khatkhate (1990) also observed the
behaviour of interest rates of 5 countries in Central Africa and declared the link between
interest rate and savings to be ambiguous. Figure 2 in appendix E shows a graphical trend
of real interest rate for deposits and domestic saving rates in each of the nine countries
studied by Nissanke. He found that no clear links are seen to exist between real interest
rates and savings rate for these countries. Hence, there is no doubt that these revelations
have interesting bearings on the issue of whether changes in interest rate can impact on
stock prices.
2.1.3 The effect of Interest Rates on Stock Prices in Emerging Markets
The economic development in most developing countries has been slow during the past
two decades compared to the western world. Per capita income in these countries grew by
less than 1% per year between 1960 and 1979. Within the last decade, more than 15
countries recorded a negative rate of growth of income per capita (Adam and Tweneboah,
2008). This dismal economic performance has largely been attributed to structural
23
weakness as well as domestic policy inadequacies. However, it is worth emphasising how
many researchers have shifted attention to look at the capital markets of some of these
developing economies due to their huge investment potential lately. Interestingly, most of
these studies were devoted to looking in to how interest rates affect stocks in these
emerging markets. Preliminary research has been carried out by numerous scholars using
different methods to investigate the relationship between stock prices and
macroeconomic variables like interest rates (Adam and Tweneboah, 2008).
In an attempt to emphasise the importance of the behaviour of interest rates as
macroeconomic variable to emerging markets like Ghana, Pill (1997) argued that interest
rates have a positive relationship with economic growth. This was explained to mean
that an economic reform program that centers on financial deregulation will permit an
increase in real rate of interest to a fairly positive, equilibrium level. A similar study
which adopted different approaches found that higher real interest rates have a positive
impact on financial activities which will in turn lead to growth and development in the
economy (Landi and Saracoglu, 1983; Gelb, 1989; Pill, 1997). Meanwhile, Asprem
(1989) argues that the positive relationship that has been heralded by most researchers
only exists in a small illiquid and financial market. Nonetheless, the argument of Shiller
and Beltratti (1992) in favour of the positive relationship is on the grounds that a change
in interest rate could carry out information about certain changes in future fundamentals
like dividends. Barsky (1989) on the hand failed to agree with the authors on their
explanation of the positive link between interest rates and stock prices and posits that the
positive relationship between interest rates and stock prices should only be attributed to
the changing risk premium. He argued that a fall in interest rates could result from an
24
increased risk being taken by investors or perhaps more investors are taking
precautionary measures by trading off risky assets (stocks) for less risky ones (bonds).
This argument is therefore in line with the view of Apergis and Eleftheriou (2001) on
their study of the Greek market. Moreover, Alagidede (2008) is of the view that the risk
perception has been the greatest obstacle to an increased access to capital in almost all
developing countries. The author thinks that the size and the illiquid nature of emerging
stock markets has been the major difference between stock market performance in
developing countries and that of the developed world.
Just as has been the norm of most academic research, several other researchers through
the use of empirical studies have come out with views which are in contrast to the views
stated above. One of such views was made known in Apergis and Eleftheriou (2001)
where the writers examined the relationship between interest rates and stock prices in
Greece and declared that an inverse relationship exists. Accordingly, the relationship
between the two is the reason why investors change the structure of their portfolios. They
pointed out that in the event of an interest rate increase, investors being rational are
expected to alter their investment portfolio to favour bonds hence a reduction in stock
prices. This is so because a decline in interest rates always leads to an increase in the
present value of future dividends (Hashemzadeh & Taylor, 1988). Additionally, the
research of Omran and Pointon (2001) investigated the effect of interest rates on the
performance of the Egyptian stock market and found that there is a long-run relationship
between interest rates and stock market performance. The writers however contend that
real rates of interest seem to have been a neglected variable in literature. In his work,
Spiro (1990) also examined the link between real interest rates and stock market
25
performance in some developing countries and concluded that an inverse relationship
exist between real rate of interest and stock market performance. In a related study, Zhou
(1996) explored the relationship between interest rates and stock prices in some selected
emerging markets using regression analysis and confirmed that interest rates have a
significant impact on stock prices, especially in the long-run. However, he disagrees with
the general view that expected stock returns move one-for-one with ex ante interest rates.
In his analysis, he explained that long-run interest rates are always the cause of the
variation in price-dividend ratios and concluded that stock market volatility is related to
the volatility of the long-term bond yields as a result of the changing forecast of the
discount rates. Quite recently, Jefferis and Okeahalam (2000) studied the stock markets
of South Africa, Botswana and Zimbabwe and observed that high interest rates in these
emerging markets always depress stock prices through the substitution effect, thus stock
prices are deemed less attractive compared to interest bearing assets such as bonds. Two
years later, Arango (2002) after studying the impact of interest rates as measured by the
interbank loan rates on the performance of the Bogota stock market discovered that an
indirect relationship exist between stock prices and interest rates but he did admit also
that the interbank loan interest rates were to some extent affected by the government’s
monetary policy initiatives. Notwithstanding, he concluded by reporting that the results
were in no way supporting efficiency on the main Columbian stock market. Hsing (2004)
repeated the studies and observed an indirect relationship between interest rates and stock
prices. However, it is worth noting that his work adopted a value at risk (VAR) model
which is structured to accommodate several endogenous variables like exchange rates,
output, real rates of interest as well as stock market index. As stipulated earlier, the work
26
of Uddin and Alam (2007) on the Dhaka Stock Exchange can be termed as a
multidimensional study. The anthors examined the relationships between interest rates
and stock prices, changes in interest rates and stock prices, interest rates and changes in
stock prices, and changes in interest rates and changes in stock prices and declared in all
cases that interest rates have a greater impact on stock prices and that changes in interest
rates have a significant negative relationship with changes in stock prices on the Dhaka
exchange.
Indeed, divergent views have been expressed on the subject under discussion in terms of
whether or not a relationship exist between interest rates and stock prices as well as the
extent of the impact of interest rate changes on stock performance on several emerging
stock markets around the globe. However, the intention here is to also find out if such
relationships exist on the Ghanaian market through an empirical framework.
2.1.4 The effects of Interest Rates on Stock Prices in Developed Markets
Like developing economies, so many views have also been aired with regards to the
interactions that exist between interest rates and stock prices in the developed world. The
ensuing discussion therefore dwells on some of the views espoused on the subject by
some scholars in an attempt to establish a relationship between interest rates and stock
prices in more advanced stock markets.
The most notable among them is the observation made by Fama (1981) in his study of the
relationship between interest rates and stock prices. The writer contends that expected
inflation is inversely related to anticipated real activity which also has a direct
relationship with stock market returns. He further stressed that stock market returns
27
should have an inverse relationship with anticipated inflation which is often proxied by
short term interest rates. Uddin and Alam (2007) on the other hand think that the effect of
long-term interest rates on stock prices starts from the present value model through the
influence of the long-term interest rates on the rate of discount. Campbell (1987) repeated
the study of Fama (1981) but instead used the yield spread and stock market returns in his
analysis in order to establish a relationship. He pointed out that the same variables that
have been employed in the prediction of excess returns in the term structure of interest
rates could also predict excess stock returns and concluded that a simultaneous analysis
of the earnings on bills, bonds and stocks should be beneficial. It is however worth
mentioning that the results of his study have been agreed to have supported the term
structure of interest rates in predicting excess returns on the stock market of US.
Thereafter, Lee (1997) tried to observe the relationship between short-term interest rates
and stock market returns by forecasting excess returns on the Standard and Poor 500
index with short term interest rates through the use of a three-year rolling regression
analysis. The author observed that the relationship is not stable over time and emphasised
there is bound to be a gradual change from a significantly negative to no relationship or
possibly a positive relationship though insignificant. Meanwhile, Officer (1973) notes
that the volatility of the market factor of the New York Stock Exchange has a direct link
with the volatility of macroeconomic variables. Harasty and Roulet (2000) studied the
stock markets of 17 developed countries and discovered that stock prices are cointegrated
with earnings as well as the long term interest rates in each of the countries studied
except that of Italy where he used short term interest rates. Yet, Schwert, (1989) is of the
view that the volatility of the returns on stock is directly related to interest rates though
28
Fama and Schwert (1997) and Geske and Roll (1983) had previously established a
negative relationship between changes in interest rates and stock returns.
Clearly, the varied studies on the relationship between interest rates and stock prices in
more advanced stock markets have been mixed just like that of the developing countries.
2.2.1 The effect of Inflation on Interest Rates
The importance of any study regarding the impact of inflation on interest rates
movements to investors and policy makers has never been in doubt (Leiderman and
Svensson, 1995; Bernanke, et al., 1998). Specifically, it is believed that timely and
accurate forecasts of inflation expectations are vital in helping monetary authorities to set
short term real rates of interest at the appropriate level as well as providing observers a
tool to analyse as to whether a central bank’s inflation targeting is credible (Bernanke, et
al., 1998). Yet, this acclaimed important subject has received very little attention in terms
of empirical evidence.
Among the very few studies which attempted to establish a relationship between the rate
of inflation and interest rates is the Fisher Effect (Fisher, 1930). In his study of the
relationship between inflation and interest rates through the International Fisher Effect,
Madura (2008) for instance used an illustration which compared two countries. He
explained that, if inflation for instance is expected to rise in the near future in Canada,
more people in Canada will want to spend now instead of saving in order to escape future
price increases. As such, they will be willing to borrow now to purchase goods before
prices go up. What this mean is that the high expected inflation leads to a small supply of
savings (loanable funds) whilst the demand for loanable funds increases hence an
29
increase in nominal interest rates. Accordingly, Canada’s nominal interest rates should
exceed the expected inflation rate in order to motivate Canadians to save.
Further, he stressed that if inflation is expected to be very moderate or fall in future in the
US, people in the United States will be more than willing to save than to spend since they
are less concerned with possible price increases due to changes in inflation. In effect,
since inflation is not a major concern, the supply of loanable funds is expected to increase
whereas the demand for loanable funds falls resulting in a decline in nominal interest
rates.
In sum, the above illustration of the Fisher effect suggests two main components of the
nominal interest rates: expected inflation rate and the real rate of interest (Madura, 2008).
The writer pointed out that the real rate of interest is equivalent to the nominal interest
rate minus the expected inflation rate. He however admitted that the real rate of interest
cannot be directly observed.
Prior to this, Mundell (1963) used the Pigou real wealth effect to establish a relationship
between the real rate of interest and expected inflation and reports that an inverse
relationship exists between the two. Similarly, the work done by Leiderman and
Svensson (1995) observe that innovations in the real rate of interest and inflation reveal a
strong negative relation which implies that nominal interest rate adjustments lag the
inflation changes and conclude his study is consistent the revelations of Barr and
Campbell (1997), Pennacchi (1991) and Summers (1983). Santomero (1973) however
contends that a change in the growth rate of labour productivity may bring about a
positive correlation between the expected real rate of interest and expected inflation but
30
admits that introducing progressive income taxes may cause further dependencies
between the variables under consideration.
2.2.2 The effect of Inflation on Stock Prices
Vast empirical literature have in no doubt cast some doubts on Fisher’s (1930)
hypothesis, which reports that nominal asset returns move directly with the expected
inflation in order for real stock returns to be determined by real factors which are
independent of the rate of inflation. In effect, Fisher (1930) is of the view that assets
which represent claims to real assets such as stocks, should offer a hedge against inflation
but empirical evidence from most studies on the relationship between stock prices and the
level of inflation especially during the period of post-world war II have been
contradictory. Various researches conducted between the periods of the 1970s and the
early 1980s (Lintner, 1975; Bodie et al., 2005; Fama and Schwert, 1977; Jaffe and
Mandelker, 1976; Nelson, 1976; Fama, 1981) and more recently Spirou (1999) have
given a clear testimony of this fact.
Apart from these, other early works also showed a negative relationship between the level
of inflation and real stock prices as the dividend price ratio reflects (Modigliani and
Cohn, 1979;
Feldstein, 1980). Similar researches quite recently by Sharpe (2002) and Campbell and
Vuolteenaho (2004) have also revealed that an inverse relationship exist between stock
prices and the rate of inflation. Rather controversially, the study of Apergis and
Eleftheriou (2001) is also in disagreement with the Fisher effect. The authors argued that
nominal interest rates do not vary exactly with inflation since they only reflect
expectations of future inflation instead of current inflation.
31
Generally, inflation seems to have a significant impact on stock prices through the effect
on future earnings as well as the manner in which investors discount their future earnings.
Clark (1993) in an attempt to explain the first channel admitted that inflation reduces
investments and future earnings thereby retarding growth on the economy. However the
emphasis of the observation made by Huisinga (1993) and Zion et al. (1993) was
centered on the ability of inflation to lower the stability of relative prices thus leading to
greater uncertainty of investment and productivity. More emphatically, there exist an
inverse relationship between uncertainty and real economic activity and this by
implication means stock prices and inflation are negatively associated (Friedman, 1977).
The writer believes that the unpredictability of inflation is noted to bring about higher
risks which are associated with investment and production processes of the corporate
sector. Schwert (1981) buttresses this point by recognising that inflation uncertainty
implies a non-optimal allocation of investment that leads to a decline in stock price.
Again, it is believed that higher inflation tends to result in higher taxes on corporate
earnings as well as higher taxes being paid by shareholders (Feldstein & Summers, 1979)
Meanwhile, the second channel stresses that the discount factor comprises two main
components which include the risk free component and that of the risk premium.
Accordingly, the latter is due to investors’ requirement of a positive return on their
capital in addition to a risk premium as a form of compensation for the risk undertaken by
investing stocks (Apergis & Eleftheriou, 2001). Finally, Malkiel (1982) posits that if
inflation could lead to a higher discount rate, then it is expected that the present value of
future earnings will decline as well as stock prices.
2.2.3 The effect of Inflation on Stock Returns
32
Many findings from empirical studies relating to the link between stock returns and
inflation are seen to be puzzling since they go contrary to economic theory as well as
common sense. For instance, the more heralded negative relation between real stock
returns and unexpected inflation is inconsistent with the classical view of monetary
neutrality where inflation cannot affect the values of real assets (Geske and Roll, 1983).
Although many attempts have been made in order to resolve the so called empirical
anomalies regarding the kind of relationship that should exist between inflation and stock
returns, it looks as if the negative relation between real stock returns and unexpected
inflation is gaining grounds with varied reasons assigned it. Feldstein and Summers
(1979) for instance pointed out that the inverse relation between real stock returns and
inflation sterns from the redistributive effect of unanticipated inflation as a result of
nominal contracting. In their explanation, the authors did contend that since taxes are
levied on nominal income in the US, higher inflation will always lead to higher tax
liability resulting in a fall of real after-tax income on equity for a given real before-tax
income. They are of the view that unexpected inflation leads to a fall in the value of
equity but stressed that rational investors only incorporate the effect of expected inflation
in valuing equity.
In a similar way, Fama (1981) did argue that the inverse relation being postulated by
several empirical researchers is spurious since stock prices and the rate of inflation are
always driven in opposite direction by random shocks in real activity. He thinks that a
positive shock in real activity should lead to an increase in the demand for money as
economic agents make adjustments to the increase in economic activity. For a given level
of money supply, the rise in the demand for money should be satisfied through a
33
reduction in current spending thereby leading to a fall in prices of commodities.
Obviously, equity prices are expected to increase with the shocks as a result of investors’
expectation of better business in the future (Fama, 1981).
The above view expressed by Fama (1981) receives support from Geske and Roll (1983)
who later demonstrates that the negative relation between real stock returns and inflation
can be replicated by a countercyclical monetary policy. However, Hasbrouck (1984)
reports that the explanation offered by Fama and Geske and Roll only emphasises the
negative correlation between real stock returns and unexpected inflation since any
covariance between inflation and real stock returns starts from random shocks to real
activities and as such must be unexpected.
A rather contrasting observation however is that unlike the numerous empirical studies on
the relation between real stock returns and unexpected inflation, literature on the
association of real stock returns and expected inflation is in limited supply. Besides this,
it is believed that the intuition behind the limited explanations offered has not been
appealing and thus lacking empirical support (Fama, 1981). For example, the implication
of the financing hypothesis by Lintner (1975) is that, firms dilute returns on equity by
raising working capital during periods of inflation in an attempt to maintain working
capital to sales ratio. However, this view has not been consistent with the observed
phenomena that firms respond aggressively to inflation increases by reducing cash
balances, tightening credit as well as delaying payments.
2.2.4 The Theory of Efficient Markets
Numerous evidence during the 1960’s show that investment strategies which are based on
detailed analysis do not actually seem to work better than simple buying and selling
34
strategies. Many attempts to explain this rationale therefore lead to the efficient market
hypothesis. The efficient market hypothesis posits that market prices of stocks already
incorporate all relevant information. Most adherents of this theory claim that this is
achieved through competition among market participants who compete for relevant
information about companies quoted on stock markets. What this means is that price
changes of stock can only be possible if new information becomes available thus
portraying the fact that prices of securities follow a random pattern since availability of
new information to the market is highly unpredictable. It is from this idea that three forms
of market efficiency have been identified based on classifications of what constitute
relevant information. These include the weak, semi-strong and the strong form of market
efficiency (Fama, 1970). Accordingly, the strong form suggests that prices of securities
reflect all private and public information. But evidence provided by Seyhun (1998) points
out that, insiders make profit from trading on information which is yet to be made
available to the public and as such the writer argues that the strong form of market
efficiency does not hold as he describes the market as an uneven playing ground. On the
other hand the semi-strong form claims that stock prices only reflect information in the
public domain. Seyhun (1998) further states that such a situation eliminates any under or
overvaluation of securities, thus going through company accounts as well as the financial
press does not give investors an upper hand in terms of profits. The point being made
here is that any new information is quickly incorporated into prices of securities (Patell
and Wolfson, 1984). With regards to the weak form of market efficiency, it suggests that
security prices are made up of all information regarding the history of that security.
However, Fama (1991) built on this idea by including predictions of future returns by
35
using accounting and macroeconomic variables. Most critics are therefore of the view
that the predictive power of the weak form of market efficiency raises doubts about its
existence. Meanwhile the whole debate surrounding the extent or the degree of market
efficiency is still ongoing. More especially, the problem of the joint hypothesis has
compounded the issue of market efficiency (Fama, 1991). According to the writer, any
tests of market efficiency should be subjected to an asset-pricing model and stressed that
any evidence to the contrary could be attributed to the fact that the market is inefficient or
incorrectness regarding the model in use.
It is highly believed that the divergent views aired on the subject provided more
theoretical basis for the majority of the financial market research in the seventies through
to the eighties (Keown & Pinkerton, 1996). Stock prices during the said period were seen
to follow a random walk model and variations in predicting stock returns if any at all
were found to be insignificant thus providing an evidence that seemed to have been
consistent with the efficient market hypothesis (Harvey, 1991). The author further
postulates that typical results from event studies only point to the fact that stock prices
adjust to new information not long after an event announcement and this as he explained
is consistent with the theory of market efficiency. Yet, many are the critics who have
raised questions that play down the existence of such a theory. Roll (1988) for instance
contends that most price movements for individual stocks cannot be related to public
announcements. A revelation similar to this is found by Cutler et al. (1989) in their
analysis of the aggregate stock market. The authors observed that the relationship
between the greatest aggregate market movement and public release of information if any
should be insignificant. Recently, analysis of the determinants of returns done by Haugen
36
and Baker (1996) in five countries discovered that none of the factors associated with the
sensitivities to macroeconomic variables were important determinants of expected stock
returns. Indeed, much of the controversy surrounding the theory has been the result of
anomalies detected in capital markets. Prominent among them is the January effect
where Rozeff and Kinney (1976) found evidence of higher returns in January as
compared to other months. As Roll (1984) puts it, these anomalies are nothing but a clear
indication that information alone does not move stock prices. It is therefore not surprising
that many researchers have resorted to investigations in order to come out with
alternative theories that can best describe stock market behaviour. Kuhn (1970) could not
therefore have put it better when he stated that discovery commences with the awareness
of anomaly.
37
CHAPTER THREE
RESEARCH METHODOLOGY
3.0 Introduction
The choice of a research method is indeed very important since it plays a very significant
role in determining the kind of conclusion that will be drawn about a phenomenon in a
given piece of research work (Miles & Huberman, 1994). Without any doubt, it has an
impact on what can be said about the cause as well as the factors affecting the
phenomenon. This chapter is basically meant to discuss the intended approach to be used
in answering the research question and to address the purpose of the study as outlined in
the introductory chapter.
As pointed out earlier, the purpose of this dissertation is to empirically examine the
impact of interest rates and the level of inflation on stock prices of the GSE All-Share
Index for the periods running from 1995 to 2009. As such, the following hypotheses are
intended to be tested to achieve this aim.
H1: There is a significant negative relationship between prices of stock and interest
rates and inflation on the GSE.
H2: There is significant negative relationship between prices of stock and interest
rates.
H3: There is significant negative relationship between prices of stock and the level of
inflation.
H4: There is significant positive relationship between interest rates and the level of
inflation.
38
Sequentially, the chapter begins by discussing the type of approach adopted for the study
followed by the kind of data utilised in carrying out this work. The research model for
data presentation will also be analysed along with the tools to be used and finally,
attention will be drawn to any limitations discovered regarding the model used.
3.1 Research Approach
This section deals with a brief discussion on the different types of approaches as well as
the research Strategy.
3.1.1 Scientific Approach
Basically, there are two main approaches that researchers adopt in an attempt to
undertake an investigation (Trochim, 2006). These are inductive and deductive
approaches. An adoption of any of the above approaches for a study depends on what the
researcher in question desires to achieve.
For instance, Bryman and Bell (2007) posit that researchers who use an inductive
approach (bottom-up) move from specific observations to a broader generalisations and
theories. This form of research is therefore based on a reasoning which transforms
specific observations into a general theory. It begins with a specific observation by the
researcher who detects a pattern and regularities, formulate tentative hypotheses which
can be explored and end up developing conclusions or theories which are general. Thus a
researcher who observes a pattern in a society may form hypotheses on it and use data
collection methods such as surveys or experiments to verify these hypotheses in order to
reach a conclusion.
39
On the contrary, researchers who use deductive approach (top-down) work by moving
from a general theory to a specific hypothesis which is suitable for testing. Here, a
researcher begins to think up a theory about a topic of interest and then narrows it down
into a more specific hypothesis that can be tested. In some instances, researchers further
narrow down theories by collecting observations to address the hypothesis which aids
them to confirm the original theories (Trochim, 2006). In summary, an inductive research
is seen to be more open-ended and exploratory in nature especially at the beginning
whereas a deductive research is narrower in nature and is about testing or confirming
hypotheses.
Since this study examines how changes in interest rates and inflation affect stock prices
based on existing theories by testing hypothesis through a review of the relevant
literature, the deductive approach is considered to be an appropriate way to objectively
answer the research question.
3.1.2 Research Strategy
The diversity in the science of research methodology paves way to discovery, growth,
and empowerment, yet it is the research itself that should determine the method of
research (Becker, 1998; Ulmer & Wilson, 2003). Undoubtedly, the research questions
and objectives should be able to give a direction as to what approach to adopt as
researchers go in search of where and how to get their data. For example, research
questions that require qualitative studies often seek to inquire into processes which are
related to change or seeking knowledge through various means while quantitative studies
typically deal with examining relationships among variables as measured by central
40
tendencies in a set of data. Studies done by Davies (2003) and Cresswell (2003) however
suggest that any research requires either qualitative or quantitative data or both.
Strauss and Corbin (1990) point out that qualitative research is a type of research that
produces findings not arrived at by means of statistical procedures or other means of
quantification. This type of research therefore follows an inductive approach. Creswell
(2003) in contrast to this view observe that quantitative methods are used mainly to verify
theories or explanations, identify variables under study, relate variables in hypothesis, use
statistical standards of validity and reliability as well as employing statistical procedures
for analysis. Hence this it follows a deductive approach of research.
Though numerous views have been given regarding the suitability of the two, Gerhardt
(2004) explains that evaluating the strength and weakness of each of the strategies in
itself involves a qualitative research. However, since this study examines how changes in
interest rates and inflation affect stock prices based on existing theories by testing
hypothesis through a review of the relevant literature, quantitative data is considered
more appropriate to objectively answer the research question.
3.2 Data
This aspect of the dissertation seeks to outline the different types of data to be used for
the analysis in an attempt to finding an answer to the research question. In addition to
this, the various sources and locations from which data is obtained will also be discussed.
3.2.1 Data Description
The main aim of this study is to look at the impact of interest rates and inflation on stock
prices of the GSE All-Share Index lasting from 1995 to 2009. To achieve this, the study
intends to employ time series data covering the stated period. The analysis of this
41
empirical study will make use of quarterly stock prices (SP) as measured by the GSE All-
Share Index, the level of inflation represented by (IF) is defined by the consumer price
index while the Bank of Ghana treasury bill rate (IR) is used as the rate of interest and all
spanning the same period. As stated earlier, the choice of the GSE All-Share Index is
purely motivated by the availability of data.
A negative relationship is expected between the rate of inflation and stock prices since
high levels of inflation lead to an increase in the cost of living by shifting resources from
investment to consumption. Further, DeFina (1991) contends that the contraction of
nominal interest rates disallow immediate adjustment of firm’s revenues and costs that
prevent cash flow to grow at the same rate as inflation. Similarly, an inverse relationship
is expected between the Treasury bill rates and stock prices since an increase in interest
rates decreases the opportunity cost of holding money and as such investors substitute the
holding of interest bearing assets for stocks leading to a fall in stock prices. However, the
Treasury bill rate is being used as a measure of interest rates in this work because
investments in Treasury bills is regarded as an opportunity cost for holding stock.
3.2.2 Data Collection
The data and other information gathered for the purpose of this study are mainly obtained
from secondary sources. Data on the theories as well as the relevant literature have are
derived from books, the internet and journals from the Glasgow Caledonian University
library’s database. Other sources include the IMF Direction of Trade Statistics Yearbook
where data on statistics were obtained, the Bank of Ghana quarterly bulletins and reports
where data on the GSE are obtained. Data on treasury bills and inflation rates were
obtained from IFS statistics. Data on stock indices were however were collected from the
42
Research department of the GSE. For the purpose of this study, nominal figures are
employed.
It is also worth noting that all time series data are quarterly values covering the period of
study which result in 60 observations. The study would have preferred monthly data to
quarterly data but the difficulty in accessing these data, demands that quarterly data be
used for the purpose of this study. However, the duration of study was chosen because it
covers the most active period of trade on the GSE. The table below provides a summary
of the various sources from which data are collected for the study.
Table 3.0: Description of source of data
Variable Concept Description Source
lnSP Natural log of GSE
All-Share Index
GSE All-Share
Index
GSE Research
lnIR Natural log of
Interest Rates
91 day Treasury bill
rates
IFS Statistics
lnIF Natural log of
Inflation
Consumer Price
Index
IFS Statistics
3.3 Model Summary
This section gives a brief discussion on the various types of models chosen and why they
have been selected for the study.
3.3.1 Model Specification
In an attempt to empirically establish a relationship between the dependent variable
(stock prices) and the independent variables (inflation rates and interest rates), several
43
tests have been carried out to test the hypotheses set out earlier in this study. A
preliminary test is done by using the ordinary least square regression analysis. However,
since regression is only effective at establishing relationships between data points which
are linear, a correlation test initially (see table 4.0) to confirm the linearity is carried out.
The results as shown by the correlation coefficients (r) are indicative of the fact that the
relationship between the GSE All-Share Index, interest rates and inflation could not be
linear. The equation one below is thus derived from the relationship between the
dependent and the independent variables.
SP = β0 * (IRt)β1 * (IFt) β2 ………………………………….....…………….……………..1
But the application of the ordinary least square regression analysis is only possible if
equation two as shown below could be established between the variables.
SPGt = β0 + β1IRt + β2IFt + e1……………………………………………..…………………….…………….……….....2
Hence, in order to make the above equation workable, the data in question is converted
by applying natural logarithm to make it linear. The conversion thus results in equation
three as indicated below.
lnSPGt = β0 + β1lnIRt + β2lnIFt + e1………………………………………………..……………………………….3
Where: lnSPGt = natural log of stock prices represented in this study by the GSE All-share
Stock Index at time t, lnIRt = natural log of interest rates at time t, lnIF t = natural log of
the rate of inflation at time t, β0, β1 and β2 = constants of the above regression equation, e1
= the white noise error term.
Secondly, another regression equation as set out below is also developed to test the
hypothesis (H2): there is a significant negative relationship between stock prices and
interest rates.
44
lnSPGt = β0 + β1 lnIRt + e1…………………………………………………………………………………...……………4
Where: lnSPGt = natural log of stock prices represented in this study by the GSE All-share
Stock Index at time t, lnIRt = natural log of interest rates at time t, β0 and β1 = constants of
the regression equation in question, e1 = the white noise error term.
In testing the third hypothesis (H3): there is a significant negative relationship between
stock prices and the rate of inflation, the regression equation established below is
adopted.
lnSPGt = β0 + β1 lnIFt + e1………………………...…………………………………5
Where: lnSPGt = natural log of stock prices represented in this study by the GSE All-share
Stock Index at time t, lnIFt = natural log of the rate of inflation at time t, β0 and β1 =
constants of the regression equation under scrutiny, e1 = the white noise error term.
Lastly, the sixth equation as seen below is applied in testing the hypothesis (H4): there is
a significant positive relationship between interest rates and the rate of inflation.
lnIRt = β0 + β1 lnIFt + e1 ………………..….….,………………………………………6
Where: lnIRt = natural log of interest rates at time t, lnIF t = natural log of the rate of
inflation at time, β0 and β1 are the constants of the above regression equation, e1 = the
white noise error term.
A confidence level of 95% at 5% significance level has been specified for the purpose of
this study. The results from the linear regression model helped in measuring the
relationship between the dependent variable and the independent variables as well as
testing the hypotheses that have been developed early on in the study. The implication of
the above equation for the study is that if all the four hypotheses are accepted then, the
test gives significant statistical evidence that the relationship between dependent and
45
independent variables is positive at 95% confidence level. On the contrary, if all the
hypotheses are not accepted, the dependent variable in the above regression equation will
be deemed to be influenced by factors other than those variables stipulated. Therefore,
Saunders et. al. (1997) suggests that p-values are key in determining whether or not the
above hypotheses should be accepted.
3.3.2 Model Justification
Arguably, the most commonly used form of regression is the linear regression. However,
the ordinary least square regression is the most common type of linear regression. It
simply makes use of values from an existing data set which consists of measurements of
the values of two variables say X and Y to develop a model that is useful for forecasting
the value of the dependent variable Y for a given value of X (independent variable) and
this obviously is in line with the objective of this study which seeks to examine the extent
to which changes in interest and inflation (independent variable) could impact on stock
price movements (dependent variable) so that analysts can make accurate predictions on
the dependent variable in future using these independent variables.
Though the ability of a linear regression to explore the relationship of an independent
variable that marks the passage of time to a dependent variable when in line has never
been questioned, Berenson et al. (2008) are of the view that multiple regressions should
be established in order for the significance and the magnitude of the effect of the
independent variables on the dependent variables to be felt and identified. Further, the R-
squared (r2) is believed to show the percentage of the total variation in the dependent
variable that is explained by all the independent variables.
46
However, the overall significance of the model can be examined by the F test which
reports a linear relationship between all of the independent variables in total and the
dependent variable, while the significance of the estimated coefficients are explained by
the t-statistics, with a threshold value of ±1.48 which is equivalent to a p-value of 0.1
(Berenson et al., 2008).
3.4 Analytical Tools
An extensive review of the relevant literature has revealed countless tests that have been
used to establish relationships between several variables. More importantly, many
statistical tests have been carried out to examine the correlation between stock prices and
a variety of macroeconomic variables. This study which seeks to examine the impact of
interest rates and inflation on the GSE All-Share Index is therefore not an exception as it
intends to use statistical methods such as SPSS in order to produce some regression
model results, descriptive statistics, correlation analysis, multicollinearity and goodness
of fit since the data collected for the purpose of this study are in the form of time
sequence.
3.4.1 Correlation Analysis
The objective of carrying correlation analysis in statistics is to determine the extent to
which a change in the value of one variable will affect the other. For instance, for the
purpose of this study, correlation analysis could be done to assess the impact that
movements or variations in interest rates and the rate of inflation could have on stock
prices.
However, it is very important to note that correlation is never causation (cause and effect
relationship) because it is possible for two attributes to be correlated but both could be
47
the cause of another variable. Nevertheless, the determination of any causal relationship
may require a very extensive experiment to be carried out. What is therefore very crucial
is that in an attempt to conduct a study such as this, there is the need to compute the
correlation coefficient (r) which measures the strength of any relationship that should
exist between the variables under study. A value of +1 depicts a positive relationship
while an inverse relationship will always be indicated by -1. However a value of zero
indicates no relationship.
3.4.2 Multicollinearity
Multicollinearity is a statistical phenomenon that occurs when there is a high correlation
between variables under consideration in such a way that it becomes very difficult to
estimate their individual regression coefficients with precision. It is therefore believed
that whenever variables exhibit such a characteristic, they are deemed to measure the
same attribute or carry the same information.
However, what should be made clear here is that multicollinearity does not in any way
reduce the predictive power of the regression model as a whole but what it does is that it
affects the individual predictors with regards to their calculations. Besides what has been
identified above, the possibility of multicollinearity among study variables could also be
assessed through correlation analysis. Thus a correlation coefficient of either 0.75 or high
among variables could be a sign of multicollinearity.
3.5 Model and Data Criticism
Linear regression analysis is very important for exploring linear relationships between
dependent and independent variables that mark a passage of time. However, whenever
the trend gets nonlinear, linear regression fails to capture any relationship between the
48
dependent and the independent variables. In addition to this anomaly, linear regression
fails to identify seasonal, cyclical, and counter cyclical trends in time series data. The
effects of changes in direction of data which are in time series as well as the rate of
change are also believed not to be captured by linear regression. Other critics are also of
the view that a problem occurs when time series values at one point can be determined or
are influenced by previous time values (Berenson et al., 2008).
Another criticism is centered on the secondary nature of the data used for the purpose of
this study considering the fact that such data are sometimes altered to suit specific
purposes. However, looking at the nature of the study, there is no way data on stock
prices, interest rates and consumer price indices could be gathered apart from the sources
identified in the study. Besides, the GSE Research is regarded as one of best when it
comes to credible sources of data in the sub-region.
49
CHAPTER FOUR
DATA ANALYSIS AND PRESENTATION OF RESULTS
4.0 Introduction
This chapter intends to analyse the data collected for this study. The study uses the
ordinary least square linear regression model. The results from the statistical tests of
significance and association of the four working hypotheses will be presented an analysed
in this chapter.
4.1 The Results
Recall that the objective of this dissertation is to establish a relationship among stock
prices, interest rates and inflation in Ghana. In order to achieve this purpose, data on the
GSE All-share Index, interest rates (Treasury bill rates), and inflation rates (CPI) for a
fifteen-year period beginning from 1995 to 2009, have been gathered (see appendix C).
The study therefore adopts the approaches of descriptive statistics, correlation and linear
regression analysis to establish linear dependence. Below is the summary of the linear
regression models for the purpose of testing the hypotheses outlined earlier in the study.
lnSPGt = β0 + β1lnIRt + β2lnIFt + e1…………………………………………….………….1
lnSPGt = β0 + β1 lnIRt + e1 ……………………………………...…………………………2
lnSPGt = β0 + β1 lnIFt + e1……………………………………..…………………………..3
lnIRt = β0 + β1 lnIFt + e1……………….….………………..……………………………4
In the above equations, β0, β1, and β2 represent the beta values or the regression coefficients
which measure the significance of the independent variables to the dependent variable. For
the purpose of this study, relationships between the dependent and the independent variables
have been established by setting the coefficients of the various regression models to a 95%
confidence level as well as a significant level of 5%. The output of the regression is therefore
50
displayed in appendix E. The application of natural log was however meant to make the data
linear.
4.2 Correlation Test Results and Analysis
The impact of one variable on another variable can be predicted with a high degree of
certainty if we can establish that the variables are correlated. As such, correlation analysis
has been done where past data of the variables under study are subjected to an initial
assessment in order to find out if there is any form of connection between them as well as
the extent of that connection. It is believed that the stronger two variables are related, the
more closely their scores will lie on the regression line and therefore the accuracy of their
prediction. Apart from this, such a test is undoubtedly very useful in identifying the high
possibility of multicollinearity between the predictor variables since such a situation can
cause problems in trying to draw conclusions about the relative contribution of each
explanatory variable to the success of the regression model. The Pearson’s coefficients of
determination are used to test the relationships between stock prices and interest rates,
stock prices and inflation and interest rates and inflation in order to quantify the direction
and magnitude of the relationship between each of the pairs. The closer the correlation
coefficient is to 1, the stronger two variables are related. A key feature of this association
is depicted in table 4.0 below where a very strong negative relationship (-0.80) is seen
between stock prices and interest rates. This could be attributed to the fact that an
increase in interest rate provides an incentive for investors to hold interest bearing
securities instead of holding stock hence the falling prices of stocks. Similarly, the
coefficient of -0.65 (rounded to two decimal places) as depicted on the same table shows
a moderate negative correlation between stock prices and the rate of inflation. The
implication of this is that as inflation goes up, stock prices fall. In contrast to these two
51
findings, a strong positive relationship is seen to exist between interest rates and the rate
of inflation according to the table. However, the magnitude of the association between
the two variables (0.73) implies an existence of multicollinearity which is likely to bring
about distortions in the results of the t-statistics and thereby leading to wrong
conclusions being established between the variables under consideration (Keller, 2005).
But as has been postulated (Dirk and Bart, 2004), the existence of multicollinearity does
not have an effect on a fitted model provided that the independent or explanatory
variables follow the same pattern of multicollinearity as the data on which the linear
regression model is related. They however pointed out that a limit of 0.75 in absolute
terms should exist before such conclusions could be valid. Hence, for the purpose of this
study, both interest rates and inflation could be used to make valid explanations of stock
prices since their coefficient of 0.73 is within this limit.
Table 4.0: Summary of results from the correlation test.
Variable lnSP lnIR lnIF
lnSP 1.00
lnIR -0.80 1.00
lnIF -0.65 0.73 1.00
4.3 Analysis and Results of Descriptive Statistics.
Table 4.1 as shown below presents the results of descriptive statistics for the data
covering stock prices, inflation and interest rates. This comprises a report of the sample
mean, median, standard deviation, skewness, range, minimum and maximum values, sum
and the number of observations. However, the discussion intends to dwell only on few of
52
the parameters mentioned above. The intention here is to try and create a mental picture
of the sort of data being utilised in the study. The high standard deviation displayed by
the GSE All-share Index gives a testimony of how volatile the stock market has been
over the years of the study. Second behind the deviation of the All-share Index is the
standard deviation of the rate of inflation which is not surprising looking at the high
inflation pressures experienced during the years under review though this could be argued
to be relatively small compared to that of the stock prices. This value is followed closely
by that of interest rates since interest rates in Ghana are heavily impacted by the level of
inflation.
Given that the data is evenly skewed judging from the table, the mean will undoubtedly
give a valid conclusion of the data when used as a measure of central tendency compared
to the median and the mode. However, the legitimacy of the mean value with regards to it
being a fair representation of the data can be questioned looking at the minimum and the
maximum values of the stock prices. Rather surprisingly such an argument could not be
made about the mean values of interest rates and inflation since a mere observation of
these figures from the table shows how evenly they are distributed.
Another interesting observation made is that though stock prices have been consistent in
terms of increases over the years, similar trends have not been witnessed with regards to
interest rates and inflation. Arguably these variables have not followed a consistent path
as depicted in table 5.0 in the appendix C.
53
Table 4.1: Summary of descriptive statistics of variables from 1995 to 2009.
Variable SP (GH. CEDI) IR (%) IF (%)
Mean 3120.86 0.27 0.23
Median 1183.57 0.26 0.17
Standard Deviation 3062.21 0.11 0.15
Skewness 0.90 -0.01 1.77
Minimum value 298.00 0.09 0.09
Maximum value 10,691.85 0.46 0.70
Sum 187,251.55 16.07 13.90
4.4 Multiple Factor Regression Analysis
An initial analysis is done through the ordinary least square multiple linear regression
analysis by using SPSS (see appendix B) to test the coefficients of all the equations
involving stock prices, interest rates and inflation. The objective is to make predictions as
to how best interest rates and inflation can explain movements in stock prices. In addition
to this, a t-statistics is also carried out to determine the relative significance of each of the
variables in the models (Sykes, 2006). In order to draw a valid conclusion with regards to
the statistical significance of the findings, the models are tested for fitness by conducting
F-statistics. A further test is done in ANOVA to determine whether any direct
manipulation of the predictor variables could cause a change in the dependent variable
contrary to what would have happened if these had not been tempered with. The
importance of these tests of significance cannot be overemphasised since they help to
determine the probability of a relationship between variables (Kennedy, 1997).
54
4.4.1 Analysis of the effects of Interest Rates and Inflation on Stock Prices
The main model employed for the study is the ordinary least square linear regression
model to test the initial hypothesis as to whether there is a significant relationship
between interest rates and inflation and stock prices. In other words, the objective of this
study is to determine whether stock prices in Ghana are mostly driven by interest rates or
inflation. In carrying out this exercise, the GSE All-share Index is used as the dependent
variable whereas Treasury bill rates and consumer price indices proxied for nominal
interest rates and inflation respectively make up the independent variables. As stated
earlier, quarterly data are used for the fifteen-year period generating a total of sixty
observations.
4.4.2 Hypothesis Testing and Analysis
In order to achieve the stated objective of the study, a linear regression at 95% confidence
level and a significant level of 5% is run. This is done to test the initial hypothesis (H1)
as to whether there is a significant relationship between interest rates inflation and stock
prices. To accept the hypothesis, the following conditions outlined below must be
evidenced;
H1: β ≠ 0, generally show the existence of a relationship.
H1: β > 0, shows a direct relationship
H1: β < 0, shows an inverse relationship
Looking at table 4.2, it is observed that the beta for interest rates is -1.65 but that of the
rate of inflation -0.29. Since none of the coefficients of determination is equivalent to
zero (β = 0), the above hypothesis should be accepted since each of them fulfils one of
the conditions above. Stated differently, a linear relationship exists between interest rates,
55
inflation and stock prices. However, the negative signs in front of these coefficients
(betas) signify an indirect or an inverse relationship between the explained variable (stock
prices) and the explanatory variables (interest rates and inflation). What this means is that
as interest rates and inflation go up, prices of stock during the years under review
decrease and vice versa. To be specific, a percentage increase in both interest rates and
inflation leads to a fall in stock prices of 1.65 and 0.29 respectively. In the case of interest
rates, the negative relationship could be attributed to the fact that an increase in interest
rates (T bills) increases the opportunity cost of holding money and as such a trade-off by
investors between stocks and interest bearing assets. The belief is that high Treasury bill
rates serve as an incentive for the public to invest in government securities (Adjasi et al.,
2008). With regards to inflation, it is seen to increase the cost of living. Moreover, an
increase in the cost of living shifts resources from investments to consumption thereby
resulting in a reduction in the demand of investment assets and consequently a fall in the
demand for stocks (Adam & Tweneboah, 2008). Besides this, it is also expected that
government will respond to the rising levels of inflation by introducing policies which
tighten the economy. For instance, the monetary policy committee could respond through
an increase in the nominal risk-free rate of interest leading to a rise in the discount rate of
the stock valuation model. The table below shows the regression results for the effect of
interest rates and the level of inflation on stock prices.
56
Table 4.2: Summary of regression results of interest rates, inflation and stock prices
Variable Coefficient T-statistic P-value Hypothesis Decision
Constant 4.61 14.99 0.000
lnIR -1.65 -6.14 0.000 H1: β ≠ 0 Accept
lnIF -0.29 -1.16 0.25 H1: β ≠ 0 Accept
R2 = 0.64, F-Statistics = 52.68, F-Probability* = 0.000, df =59, Adjusted R2 = 0.63
The above scenario can best be described by catching a glimpse of figure 4.1 as seen
below. This typically depicts the inverse relationship between interest rates and stock
prices for the period being reviewed. It could be observed that stock prices are showing
very low figures during the early 1990’s when interest rates peaked. For instance, prices
of stock showed a figure of 298.00 in the first quarter of 1995 which is an all-time low
considering the period of study when interest rates peaked relatively at 33%. Contrary to
this, stock prices rose to an unprecedented 4,818 Ghana cedis in 2006 when interest rates
stood at only 9.53%. Similarly, a plot of inflation rates against stock prices as represented
by figure 4.2 leads to a result similar to that of interest rates as portrayed by the beta
values shown on the above table. The regression model derived from the above table is
thus stated as:
lnSPGt = 4.61-1.65 lnIRt - 0.29 lnIFt + et. …………………………………….………………………………………1
Further tests are therefore carried out to determine how well the above model fits the data
gathered for the fifteen-year period. An overall fitness is checked by using the F-statistics
along with the Fischer distribution. The purpose of this test is to check the statistical
significance of the regression equation above. Usually an F-value which is bigger than
4.0 is deemed significant hence with 95% confidence level, it can be concluded that the
57
model aids an understanding of the interaction between stock prices, interest rates and
inflation as depicted on the table above. Moreover, a small p-value of approximately
0.000 above provides evidence that at least one of the independent variables is important
in explaining the variations in stock prices in Ghana thereby suggesting the acceptance of
the hypothesis that there is a significant relationship between stock prices, interest rates
and inflation. Another way of discovering the significance of the regression model to the
study is the R2. It tells the percentage of variation in stock prices explained by interest
rates and the level of inflation. Normally, its values range from 0 to1 but a higher R2
value is an indication of a good fit for the data by the model. Again with an R2 value of
0.64, it can be concluded confidently that the model is valid.
Having confirmed the validity of the regression model, a test to find out the relative
importance of each of the predictor variables is conducted. In other words, there is the
need to find out whether it is interest rates or inflation that does a better job in explaining
movements in stock prices. Generally, any explanatory variable that has zero as its
coefficient is regarded not to contribute meaningfully in predicting the value of the
variable which is being explained. Nonetheless, a close look at table 4.2 indicates that
each of the independent variables at least plays a role towards the variation in stock
prices. However, what is certain therefore is that the degree of importance of interest
rates and inflation to movements in stock prices vary looking at their coefficients from
the regression model. A t- statistics is then conducted to establish the relative importance
of interest rates and inflation on stock price movements. As a general guide, a t-value
which is bigger than 2 in absolute terms signifies the importance of the independent
variable to the dependent variable. Hence, t-values of 6.14 and 1.16 for interest rates and
58
inflation respectively indicate that comparatively, stock prices in Ghana are driven not by
inflation but by interest rates which contrasts the findings of Apergis and Eleftheriou
(2001) who conducted a similar study on the Athens stock market and concluded that
Greek stocks are driven by inflation. Therefore, with a confidence level of 95%, it can be
concluded that interest rates exert greater influence on stock price movements in Ghana
as compared to inflation. But, there is 5% possibility of deviation from normal as far as
this prediction is concerned. Yet, further to this assertion is the belief that t-values when
used provide more accurate prediction in comparison with regression coefficients since it
factors in the error. However, the revelation of this study follows the findings of Firth
(1979); Luintel and Paudyal (2006) and Adam and Tweneboah (2008) at a confidence
level of 95%.
4.5 Single Factor Regression Analysis
This section of the chapter presents a critical analysis of the results of the single factor
regression model. This comprises the test of hypotheses two to four as presented earlier
in the study.
4.5.1 Analysis of the effects of Interest rates on Stock prices
The review of the numerous literature regarding the relationship between interest rates
and stock prices indeed has provided divergent views as to the direction of movement but
what is certain is that most analysts seem to agree that interest rates have a significant
impact on stock prices. For instance, the study of Apergis and Eleftheriou (2001) found a
positive relationship between stock prices and interest rates but concluded that the
relationship is statistically insignificant. In an attempt to test the hypothesis of whether
59
there is a significant relationship between interest rates and stock prices in Ghana, the
regression model below is derived (see Table 4.3).
lnSPGt = 4.76 –1.88lnIRt+e1………………..….................................................................. 2
Below is a presentation of the summary results of the regression of interest rates on stock
prices.
Table 4.3 Summary regression results for stock prices and interest rates
Variable Coefficient T-statistics P-value Hypothesis Decision
Constant 4.76 17.06 0.000
IR -1.88 -10.17 0.000 H2: β ≠ 0 Accept
R2 = 0.64, F-Statistics = 103.43, F-Probability* = 0.000, df =59, Adjusted R2 = 0.63
An initial conclusion as to the relationship between interest rates and stock prices is
drawn by analysing the correlation test results presented earlier in the study. The R value
of -8.0 shown by the result indicates a strong negative relationship between interest rates
and stock prices. This is seen to be consistent with the result established by the single
regression model presented above both in direction and in magnitude. The coefficient of
determination displayed by the single regression model as presented in table 4.3 confirms
how significant statistically interest rate is to the movement of stock prices. It also an
indicative of the fact that an indirect relationship exists between the two variables. This
trend is best portrayed by figure 4.1 below over the period of the study.
60
31 Dec. 09
31 Dec. 08
31 Dec. 07
31 Dec. 06
31 Dec. 05
31 Dec. 04
31 Dec. 03
31 Dec. 02
31 Dec. 01
31 Dec. 00
31 Dec. 99
31 Dec. 98
31 Dec. 97
31 Dec. 96
31 Dec. 95
05
101520253035404550
0.00
2000.00
4000.00
6000.00
8000.00
10000.00
12000.00graph of interest rates and stock prices
Interest RatesStock Index
interest rates
dates
stock prices
The above figure clearly shows that the performance of GSE All-Share Index was not
very encouraging from 1995 to 2003 when interest rates were at their peak. This because
attractive interest rates favour investments in interest bearing assets such bonds.
However, the story was different after 2003 as depicted above indicating clearly an
indirect relationship between the two variables.
Also, a close observation of table 4.3 shows an F-value of 103.43 which is highly
significant statistically compared to the benchmark value of 4.0. Therefore, it can be
concluded that interest rates provide meaningful explanation to the movement in stock
prices. Put differently, it can be said that the regression equation involving stock prices
and interest rates will be very useful to investors when used as basis for making
investment decisions but at an error level of 5%. Besides the F-value, the p-value of
approximately 0.000 indicates that the prediction of stock prices in Ghana based on
interest rates will be correct at 95% level of confidence. Again, the significance of R 2 is
indeed a confirmation of the important role that interest rates play in explaining
61
variations in stock prices. To be specific, the value of 0.64 representing R2 on the table
above signifies that about 64% of the variation in the GSE All-share Index is caused by
interest rates all things being equal.
This finding is similar to that of Adam and Anokye (2008) in their study of the impact of
macroeconomic variables on stock prices in Ghana but contrary to the conclusions drawn
by Asprem (1989); Barsky (1989) and Shiller and Beltratti (1992) who state that there
exist an insignificant relationship between stock prices and interest rates.
4.5.2 Analysis of the effects of Inflation on Stock Prices
Like the relationship between interest rates and stock prices, the study of the impact of
inflation on stock prices has attracted extensive and varied views. However, the review of
the literature revealed that not much of such studies are done in emerging markets like
that of Ghana. This therefore has been the motivation behind the test of the hypothesis as
to whether a significant relationship exists between inflation and the GSE All-share
Index. The findings of this work began by doing a correlation test depicted in table 4.1
above. The table shows -0.65 as the correlation coefficient depicting a moderate
association between inflation and stock prices. Thus unlike the correlation between stock
prices and interest rates which is deemed to be very strong, inflation does not have much
impact on stock prices in Ghana. Nonetheless, the direction of movement by the two
explanatory variables has been consistent throughout the study as shown by the negative
sign preceding their coefficients. In addition to the correlation test, a single model
regression analysis is also run to further determine the impact of inflation on stock prices.
The results of the analysis has been summarised on table 4.4 below.
Table 4.4: Summary of regression results of the impact of inflation on stock prices
62
Variable Coefficient T-statistics P-value Hypothesis Decision
Constant 5.13 13.57 0.000
IF -1.43 -6.44 0.000 H3: β ≠ 0 Accept
R2 = 0.41, F-Statistics = 41.49, F-Probability* = 0.000’ df =59, Adjusted R2 = 0.41
Based on the table above, the regression model below is derived:
lnSPGt = 5.13 - 1.43 lnIFt + e1………………………………………................................. 3
A quick look at the table above depicts an F-value of 41.49 at 0.000 probability which is
highly significant when compared to the standard value of 4.0. This thus confirms the
validity of the model as a best fit for the data. The implication is that inflation plays a role
in explaining the variation of stock prices in Ghana but not as significant as interest rates.
In order to be double sure of this conclusion, the analysis is extended to cover the use of
R2. The value 0.41 shown beneath table 4.4 for R2 implies that only 41% of the variation
in the GSE All-share Index can be accounted for by variations in inflation. Though this
revelation casts some doubts on the reliability of inflation in predicting stock movements
by investors, the small p-value of approximately 0.000 produced by this analysis is rather
encouraging. This value suggests that inflation is statistically significant regarding its
impact on the GSE All-share Index hence also suggesting the acceptance of the
hypothesis that inflation has an impact on stock price in Ghana though not very
significant compared to interest rates. Besides these, the t-statistics for the regression co-
efficient, of 6.44 in absolute terms significantly differs from zero at 95% confidence level
hence implies that inflation contributes significantly to the variations in the GSE All-
share Index. Nonetheless, figure 4.2 below is an indicative of the fact that the relationship
63
between inflation and stock prices is similar to that of interest rates and stock prices
regarding the direction of movement.
31 Dec. 09
31 Dec. 08
31 Dec. 07
31 Dec. 06
31 Dec. 05
31 Dec. 04
31 Dec. 03
31 Dec. 02
31 Dec. 01
31 Dec. 00
31 Dec. 99
31 Dec. 98
31 Dec. 97
31 Dec. 96
31 Dec. 95
01020304050607080
0.00
2000.00
4000.00
6000.00
8000.00
10000.00
12000.00
graph of inflation and stock prices
Inflation RatesStock Index
dates
inflation rates
stock prices
The above simply shows that the rational investor will trade-off stocks for interest
bearing securities in an environment of high inflation pressures.
The conclusion drawn here is consistent with that of Fisher’s (1930) hypothesis which
acknowledges an impact of inflation on stock prices but departs from this study regarding
the direction of movement. Contrary to the negative relationship established in this study
between the two variables, Fisher (1903) is of the view that inflation should move one-
for-one with stock prices in order for stock prices to provide a hedge against inflation.
Yet many findings as revealed by the extensive review of the related literature violate this
view.
4.5.3 Analysis of the effect of Inflation on Interest Rates
64
This section of the study tries to look at the relationship between the two predictor
variables (inflation and interest rates) in order to assess the impact such a relationship is
likely to bring on the dependent variable (stock prices). The preliminary assessment of
such linkage is done through the use of correlation test results depicted in table 4.1 earlier
in the study. The correlation coefficient of 0.73 clearly indicates how strong inflation and
interest rates are related. Apart from being highly related, the correlation coefficient (r)
signifies a positive relationship between the two variables. This therefore implies that an
increase in inflation brings about a corresponding increase in interest rates and vice versa
all things being equal. This trend is also clearly depicted in figure 4.3 as shown below.
31 Dec. 09
31 Dec. 08
31 Dec. 07
31 Dec. 06
31 Dec. 05
31 Dec. 04
31 Dec. 03
31 Dec. 02
31 Dec. 01
31 Dec. 00
31 Dec. 99
31 Dec. 98
31 Dec. 97
31 Dec. 96
31 Dec. 95
01020304050607080
05101520253035404550
graph of interest rates and inflation
Inflation RatesInterest Rates
dates
interest rates
inflation rates
The figure above indicates that the monetary policy committee of the Bank of Ghana is
more often than not tempted to adjust interest rates upwards whenever inflation is high
and vice versa. The relationship is therefore direct.
To find out about the magnitude of increase or a decrease any change in inflation could
bring on interest rates, interest rates are regressed on the level of inflation. The summary
results of the regression on interest rates and inflation is presented below in table 4.5
65
Table 4.5: Summary results of the impact of inflation on interest rates
Variable Coefficient T-statistics P-value Hypothesis Decision
Constant -031 -2.17 0.034
lnIF 0.69 8.12 0.000 H4: β ≠ 0 Accept
R2 = 0.53, F-Statistics = 65.88, F-Probability* = 0.000, df =59, Adjusted R2 = 0.52
The following regression model is therefore derived from the above table:
lnIRt = -0.31 + 0.69 lnIFt + e1……………....................................................................... ..4
In effect, what the above model portrays is that a percentage increase in inflation leads to
a change of 0.69 in interest rates suggesting the acceptance of the hypothesis which states
that a significant relationship exist between interest rates and inflation. This confirms the
consistency of the results of both the correlation test as well as the regression test with
regards to the link between the two variables. Further to these tests, R2 shows a value of
0.53 which implies that about 53% of the variation in interest is attributable to inflation
changes. In addition, the significance of the F-value of 65.88 goes to explain how
important inflation is in explaining changes in interest rates. Another strong point that
could be made regarding the strength of the correlation between interest rates and
inflation is the p-value from the above table. Interestingly the results of this study seem to
agree with the findings of Fisher (1930) as well as that of Madura (2008) who built on
Fisher’s hypothesis in his analogy as reflected already in the literature above. However,
for the purpose of this study, the degree to which interest rates is correlated to inflated
could possibly have a negative impact on the overall outcome as regards the objective of
the study due to the presence of mulcollinearity.
66
CHAPTER FIVE
5.0 Discussions and Conclusion
The role of the stock market in economic development is indeed one of the most
controversial and well-debated subjects in the world of finance and economic theory.
While its contributions have been very crucial towards the development of most
developed economies, such cannot be said about the role it plays in developing markets.
It is therefore with this conviction that this dissertation seeks to investigate the factors
that are responsible for movements in stock prices in a developing economy like Ghana
so that policy makers can take into consideration these factors in formulating policies
with a view to fostering economic development.
The study as stated earlier, is intended to determine the effect of interest rates and
inflation on the GSE All-share index covering the periods from 1995 to 2009. For this
purpose, quarterly data on the All-share index (stock prices) were utilised as the
dependent variable whereas the Treasury bill rates and the consumer price index proxied
for interest rates and inflation respectively were used as the independent variable.
Basically, the study employed regression, descriptive statstics and correlation to examine
the impact of interest rates and inflation on stock prices. The results of both the
correlation and regression tests revealed that the GSE All-share index is inversely related
to interest rates and inflation. The implication of this revelation is that the stock prices of
Ghana do well under conditions of low interest rates and for that matter inflation. Besides
this and perhaps most importantly, the study also revealed although both interest rates
67
and inflation account for variations in stock prices, the impact of inflation on stock price
movement in Ghana is insignificant as compared to interest rates. Therefore, the
empirical evidence presented by the study above is suggestive of the fact stock prices in
Ghana are driven primarily by interest rates and not inflation all things being equal in
spite of the close relationship established between the two independent variables in the
study. This conclusion however implies that substantial increases in stock prices with the
resultant higher economic growth can only be achieved if proper policies are put in place
by policy makers to ensure that interest rates are kept at their lowest level possible.
5.1 Implications and Recommendations
It is worth noting that interest rates and inflation have attracted much attention in
financial economics in both developed and developing economies because of their
implications in financial markets and most importantly the stock market. However, so
many variables apart from interest rates and inflation can have a significant impact on
stock prices.
In effect, what this finding is suggesting is that though the empirical evidence of this
study could be used as basis for making investment decisions, investors and corporate
management are advised to analyse other macroeconomic variables critically since these
variables when considered could make a significant impact to the outcome of the study.
Nevertheless, interest rates and inflation are believed to increase the value of the firm via
its stocks in the long term, but it important to stress once again the two variables only
form a small percentage of the factors that can influence movements of stock prices in
Ghana. This therefore goes to suggest that a fall in interest rates does not necessarily
mean that stock prices will go up and vice versa. Yet the importance of these two
68
variables in such a study cannot be overemphasised. It is therefore recommended that the
monetary policy committee of the Bank of Ghana (BoG) should adopt the appropriate
interventionist strategies at the right times to ensure these factors are stabilised for
economic growth to thrive. On the other hand regulators of the stock market are also
expected to benefit from these findings since the factors that influence the movement of
stock in itself is an important step towards a sound regulatory framework as regards the
stock market.
5.2 Limitation of Study
Like many other studies carried out, this study has its own short comings and limitations
that admittedly, could have an impact on its findings. Recall that only interest rates and
inflation were employed in this study as the explanatory variables but in reality, stock
prices are affected by many variables other than those used. Other macroeconomic
variables such as exchange rates, foreign direct investment, trade deficit and money
supply are noted to cause variations in stock prices. This study is therefore susceptible to
the omitted variable bias as the many omitted variables become part of the noise term.
Besides this, the ability of the regression equation to capture relationships between the
dependent and the independent variables in situations where the dependent variable over
time is nonlinear could be questioned. It is noted that the GSE All-share index though
sought from a reliable source could be a victim of such circumstances.
Furthermore, the possibility of multicollinearity cannot be overemphasised. Both the
correlation and regression tests conducted revealed high correlation between interest rates
69
and inflation and since these two variables are independent of the analysis, being highly
related could potentially affect the findings.
Finally, the secondary nature of the data gathered as well as the estimation of the t-
statistics which is deemed too simple to be able to illustrate any calculation of statistical
significance is also identified.
5.3 Validity and Reliability
Validity in a quantitative research such as this seeks to find out if the instrument used in
the research actually measures what the researcher intends to evaluate (LaCoursiere,
2003). Hence, a research is said to be valid if its measure is scrutinised to ensure it is
applicable under varying circumstances using probabilities. However, the flexibility with
which the models were applied as well as the accuracy of the data collected from GSE
and the IMF database raises no question marks about the credibility of the study.
The validity of the study makes it reliable as well. Though often used in conjunction with
validity, reliability simply means the rate at which the outcome of the study could be
repeated in case it is replicated (Ulmer & Wilson, 2003). Having used SPSS to analysed
the data which were collected from very credible sources and the fact that the findings
have been consistent with conclusions drawn from other researches as revealed by the
literature means that the work is reliable.
Besides also being reliable, the results can be generalised with regards to the relationship
between interest rates and inflation and their impact on stock prices and how investors
should be expected to react towards changes in any of these variables.
5.4 Suggestions for further Study
70
The findings of this work have been consistent but for future studies purposes, other
researchers may wish to take into consideration several other macroeconomic variables
since the limited number of variables used in this study have been cited as a limitation.
Finally, it is being suggested that this research is repeated in other emerging markets
using similar data over the period of this study in order to establish the consistency or
otherwise of the study.
References:
1. Adam, A.M and Tweneboah, G., 2008. Macroeconomic Factors and Stock
Market Movement: Evidence from Ghana. [Online]. Available from:
http://mpra.ub.uni-muenchen.de/11256/1/MPRA_paper_11256.pdf [Accessed 7th
January 2011]
2. Adjasi, C., Harvey, S.K. and Agyapong, D., 2008. Effect of Exchange Rate
Volatility on the Ghana Stock Exchange. [Online]. Available from:
71
http://www.globip.com/pdf_pages/african-vol3-article3.pdf [Accessed 9th
January 2011]
3. Agenor, P. and Montiel, P.J., 1996. Development Macroeconomics. [Online].
Available from: http://press.princeton.edu/titles/6821.html [Accessed 5th January
2011]
4. Alagidede, P., 2008. How integrated are African Financial Markets with the rest
of the World?, EEFS Conference Paper.
5. Apergis, N and Eleftheriou, S., 2002. Interest rates, inflation, and stock prices:
case of the Athens Stock Exchange. Journal of Policy Modelling. Vol. 24
pp.231–236.
6. Arango, L. E., Gonzalez, A. and Posada, C. E., 2002. Returns and interest rate: A
nonlinear relationship in the Bogotá stock market. Applied Financial Economics,
12(11), 835-842.
7. Asprem, M., 1988. Stock prices, Asset portfolio, and microeconomic variables in
ten European Countries. Journal of Banking and Finance Vol. 13 pp. 589-612.
8. Barr, D. G. and Campbell, J.Y., 1997. Inflation, Real Interest Rates, and the
Bond Market: A Study of UK Nominal and Index-linked Government Bond
Prices,. Journal of MonetarEconomics, 39, 361-383.
9. Barsky, R., 1989. Why don’t the prices of stocks and bonds move together?
American Economy Review, Vol. 79, pp.1132–1145.
10. Becker, H., 1998. Tricks of the trade: How to think about your research while
you’re doing it. Chicago: University of Chicago Press
72
11. Benita, G. and Lauterbach, B., 2004. Policy Factors and Exchange Rate
Volatility: Panel Data Verses a Specific Country Analysis, Research Unit,
Foreign Exchange Activity Department, Bank of Israel, Jerusalem.
12. Berenson, M. L., Levine, D.M. and Krehbiel, T.C., 2008. Basic Business
Statistics. 11th edition. New Jersey: Prentice Hall.
13. Bernanke B., T. Laubach, F. S. Mishkin and A. S. Posen, 1998, .In.ation
Targeting,.Princeton University Press.
14. Bionomicfuel.com., 2010. Stock market newsletter for strategies and ideas.
[Online]. Available from: http://www.trade-alerts.com/?
gclid=CLrewru4zqcCFUEa4Qod3R0vCg [Accessed 6th January 2011]
15. Bodie, Z., Kane, A. and Marcus, A.J., 2005. Investment, 6th edition, McGraw
hill, Singapore
16. Bryman A. and Bell, E., 2003. Business Research methods. Oxford University
Press Inc, New York.
17. Campbell, J. Y., 1987. Stock returns and the term structure. Journal of Financial
Economics, Vol. 18, No. 2 pp.373-399.
18. Chen, N. F., Roll, R. and Ross, S. A., 1986, Economic Forces and the Stock
Market, Journal of Business, Vol 59, pp.383-403
19. Cheung, Y. and Ng, L., 1998. International evidence on the stock market and
aggregate economic activity, Journal of Empirical Finance, 5, 281-296.
20. Chuppe, T.M. and Atkin, M., 1992. Regulation of securities market: Some recent
trends and their implications for emerging markets. Economics Dept.,
International Finance Corp., Washington DC.
73
21. Clark, T.E., 1993. Cross-country evidence on long-run growth and inflation.
Working paper, Federal Reserve Bank of Kansas City.
22. Corbin, J. and Strauss, A., 1990. Grounded theory research: Procedures, canons,
and evaluative criteria. Qualitative Sociology, 13(1), 3-21.
23. Creswell, J., 2003. Research Design. Thousand Oaks, CA: Sage Publications.
24. Cutler, D.M., Poterba, M. and Summers, L.H., 1989. What moves Stock Prices,
Journal of Portfolio Management 15, 4-12
25. Dailami, M., 1992. Reviving Investment in Developing Countries: Empirical
Studies and Policy Lessons. [Online]. Available from:
http://www.allbookstores.com/Reviving-Private-Investment-Developing-
Countries/9780444893956 [Accessed 15th January 2011].
26. Davis L. E., Larry N. and Eugene N. W., 2003. How It All Began: The Rise of
Listing Requirements on the London, Berlin, Paris, and New York Stock
Exchanges, The International Journal of Accounting, 38:2 (Summer), pp. 117-
143.
27. DeFina, R.H., 1991. Does Inflation Depress the Stock Market?, Business Review,
Federal Reserve Bank of Philadelphia, 3-12.
28. Dirk, V. and Bart, L., 2004. Attrition Analysis for Financial Services Using
Proportional Hazard Models, European Journal of Operational Research, Vol.
157 No. 1, pp.196-217
29. Dornbush, R., and Reynoso, A., 1989. Financial factors in economic
development, The American Economic Review.
74
30. Fama, E., 1970. Efficient Capital Market: A Review of Theory and Empirical
Tests, Journal of Finance, Vol. 25, pp.3852, 417.
31. Fama, E.F., 1981. Stock Returns, Real Activity, Inflation and Money, American
Economic Review 71, 545-565
32. Fama, E., 1991. Efficient Capital Markets:II, Journal of Finance 46 1575-1617.
33. Fama, E. and French, K., 1995. Size and book-to-market factors in earnings and
returns, Journal of finance 50, 131-155.
34. Fama, E.F. and Schwert, G.W., 1977. Asset Returns and Inflation, Journal of
Financial Economics 5, 115-46.
35. Feldstein, M. and Summers, L., 1979. Inflation and the taxation of capital income
in the corporate sector. National Tax Journal, 32, 445–470.
36. Firth, M., 1979. The Relationship between Stocks Market Returns and of
Inflation, Journal of Finance 34 (June 1979).
37. Fisher, I., 1930. The Theory of Interest, Macmillan, New York.
38. Frank, P. and Young, A., 1972. Stock Price Reaction of Multinational Firms to
Exchange Realignments, Financial Management, Winter, pp.66–73, Principles of
Economics, New York, McGraw Hill/Irwin.
39. Friedman, M., 1977. Nobel lecture: Inflation and unemployment. Journal of
Political Economy, 85, 451–472.
40. Gelb, A.H., 1989. Financial Policies, Growth and Efficiency, World Bank
Working Paper, No. WPS 202, (Washington D.C.: World Bank).
41. Gerhardt, P.L., 2004. Research Methodology Explained for Everyday People.
[Online]. Available from:
75
http://www.paulgerhardt.com/homework/RESEARCH_METHODOLOGY_EXP
LAINED_FOR_EVERDAY_PEOPLE.pdf [Accessed 10th February 2011]
42. Geske, R. and Roll, R., 1983. The fiscal and monetary linkage between stock
returns and inflation, Journal of Finance 38, 1-33.
43. Ghana Stock Exchange, Fact Books, Various Publications, Accra – Ghana.
44. Ghana Stock exchange Quarterly Report, June 2007
45. Glen, J., 1995. International Comparison of Stock Trading Practices, World
Bank conference on Stock Markets, Corporate Finance, and Economic Growth
Goldsmith, R.W. 1969. Financial Structure Development, Yale University Press,
New Haven.
46. Glower, C. J., 1994. Interest rate Deregulation, Asian Development Bank,
Occasional Papers No. 9.
47. Gosnell, T.F., Keown, A.J. and Pinkerton, J.M., 1996. The intraday speed of
stock price adjustment to major dividend changes: Bid-ask bound and order flow
imbalances, Journal of Banking and Finance 20, 247-266.
48. Harasty, H. and Roulet, J., 2000. Modelling Stock Market returns. Journal of
Portfolio Management. Vol 26 No. 2 pp33-349.
49. Harvey, C.R., 1991. The world price of covariance risk, Journal of Finance 46,
111-157.
50. Haugen, R.A. and Baker, N.L., 1996. Commonality in the determinants of
expected stock returns, Journal of Financial Economics 41, 401-439.
51. Hasbrouck, J., 1984. Stock Returns, Inflation, and Economic Activity: The
Survey Evidence, Journal of Finance, Vol. 39, 1293-1310.
76
52. Hashemzadeh, N. and Taylor, P., 1988. Stock prices, money supply, and interest
rate: The question of causality. Applied Economics, 20, 1603–1611.
53. Hsing, Y., 2004. Impacts of Fiscal Policy, Monetary Policy, and Exchange Rate
Policy on Real GDP in Brazil: A VAR Model. Brazilian Electronic Journal of
Economics, 6 (1).
54. Huizinga, J., 1993. Inflation uncertainty, relative price uncertainty, and
investment in US manufacturing. Journal of Money, Credit, and Banking, 25,
521–549.
55. Humpe, A., and Macmillan, P., 2007. Can Macroeconomic Variables Explain
Long Term Stock Market Movements? A Comparison of the US and Japan,
CDMA Working Paper No. 07/20
56. Imperial Gazetteer, 1931. The Imperial Gazetteer of India. [Online]. Available
from:
http://dsal.uchicago.edu/reference/gazetteer/ [Accessed 7th January, 2011]
57. Jaffe, J and Mandelker, G., 1976. The Fisher Effect for Risky Assets: An
Empirical Investigation. Journal of Finance 31, 447-58.
58. Jefferis, K. R. and Okeahalam, C. C., 2000. The Impact of Economic
Fundamentals on Stock Markets in Southern Africa. Development Southern
Africa, 17(1), 23-51.
59. Jone, M. and Bacon, R., 2007. Surprise Earnings announcement: A test of market
efficiency. Proceedings of the Academy of Accounting and Financial Studies,
Volume 12, Number 1.
77
60. Jones, L.E., Rodolfo E. M. and Peter E. R., 1993, Optimal Taxation in Models of
Endogenous Growth, Journal of Political Economy, 485-517.
61. Keller, G., 2005. Statistics for Management and Economics. 7th ed. Thomson,
Belmont, CA, USA.
62. Kennedy, P., 1985. A Guide to Econometrics. [Online]. Available from:
http://www.filestube.com/a/a+guide+to+econometrics+peter+kennedy [Accessed
25th February 2011]
63. Kuhn, T.S., 1970. The Structure of Scientific Revolution. University of Chicago
Press.
64. Kwon, C.S. and Shin, T.S., 1999. Cointegration and Causality between
Macroeconomic Variables And Stock Market Returns Global Finance Journal,
1999 Vol. 10, No. 1, pp. 71-81.
65. LaCoursiere, S., 2003. Research methodology for the internet. Advances in
Nursing Science, 26(4), 257-273.
66. Lee, W., 1997. Market timing and short-term interest rates. Journal of Portfolio
Management, 23 (3), 35-46.
67. Leiderman, L. and Svensson, L.E.O., 1995. Inflation Targets. Center for
Economic Policy Research.
68. Lintner, J., 1975. Inflation and Security Returns. Journal of Finance 30, 259-80.
69. Landi, A. and Saracoglu, A., 1983. Interest Rate Policies in Developing
Countries", International Monetary Fund Occasional Paper, No. 22.
70. Luintel, K.B. and Paudyal, K., 2006. Are Common Stocks A Hedge against
Inflation? Journal of Financial Research XXIX, (1), 1–19.
78
71. Madura, J., 2008. International Financial Management. 9th ed. Thomson
Learning Center, USA.
72. Malkiel, B. G., 1982. US equities as an inflation hedge. In Boeckh, J. A. &
Coghlan, R. T. (Eds.), The Stock market and inflation. Homewood: Dow Jones-
Irwin.
73. Maysami, R. C. and Koh, T. S., 2000. A Vector Error Correction Model of the
Singapore Stock Market, International Review of Economics and Finance 9, 79 –
96.
74. McClure, B., 2010. How Interest Rates Affect the Stock Market. [Online].
Available from:
http://www.investopedia.com/articles/06/interestaffectsmarket.asp [Accessed
20th February, 2011]
75. McKinnon R. I., 1973. Money and Capital in Economic Development, The
Brookings Institute, Washington, D.C.
76. Miles, M. B. and Huberman, A. M., 1994. Qualitative Data Analysis. Thousand
Oaks, Sage.
77. Modigliani, F. and Cohn, R. A., 1979. Inflation, rational valuation, and the
market. Financial Analysts Journal, Vol. 38, pp.24–44.
78. Mukherjee, T. and Naka, A., 1995. Dynamic Relations Between Macroeconomic
Variables and the Japanese Stock Market: an Application of a Vector Error
Correction Model", Journal of Financial Research, XVIII (2), 223-237.
79. Mundell, R., 1963. Inflation and Real Interest. Journal of Political Economy, 71,
280-283.
79
80. Nelson, C. R., 1976. Inflation and rates of return on stocks, Journal of Finance,
31:2, 471-83.
81. Nissanke, M., 1990. Mobilizing domestic resources for African development and
diversification; structural impediments in the formal financial system, mimeo,
Oxford, June.
82. Officer, R.R., 1973. The variability of the market factor of New York Stock
Exchange, Journal of Business, 46, 434-453.
83. Ologunde, A.O., Elumilade, D.O. and Asaolu, T. O., 2006. Stock Market
Capitalization and Interest Rate in Nigeria: A Time Series Analysis.
International Research Journal of Finance and Economics, 4, 154-166.
84. Omran, M. and Pointon, J., 2001. Does the Inflation Rate Affect the Performance
of the Stock Market? The Case of Egypt", Emerging Market Review, 2 (3), 263-
279
85. Patell, J and Wolfson, M., 1984. The Intraday speed of adjustment of stock prices
to earnings and dividend announcements, Journal of Financial Economics 13,
223-252.
86. Pennacchi, G. G., 1991. Identifying the Dynamics of Real Interest Rates and
In.ation: Evi dence Using Survey Data,.Review of Financial Studies, Vol 4, No.
1, 53-86.
87. Pill, H., 1997. Real Interest Rates and Growth: Improving on Some Deflating
Experience, Journal of Development Studies, 34 (1), 85-111.
88. Ploeg, F.V., 1996. Budgetary Policies, Foreign Indebtedness, the Stock Market,
and Economic Growth, Oxford Economic Papers, 48 (3), 382-397.
80
89. Popiel, P.A., 1988. Development of Money and Capital Markets-Economic
Development Institute, World Bank working papers.
90. Roll, R., 1984. Orange juice and weather, American Economics Review 74, 861-
880.
91. Roll, R., 1988. R2, Journal of Finance 43, 541-566
92. Rozeff, M.S. and Kinney, W.R. (1976). Capital market seasonality: The case of
stock returns, Journal of Financial Economics 3, 3798-402.
93. Santomero, A.M., 1973. A Note on the Interest Rates and Prices in General
Equilibrium. Journal of Finance 38, 997-1000.
94. Saunders, M. and Cornett, M., 2008. Financial Institutions Management: A risk
Management Approach. McGraw-Hill Irwin. NY. USA.
95. Saunders, M., Lewis, P. and Thornhill, A., 1997. Research Methods for Business
Students. Pitman Publishing, London.
96. Schwert, P., 1981. The adjustment of stock prices to information about inflation.
Journal of Finance, 36, 15–29.
97. Schwert, G. W., 1989. Why Does Stock Market Volatility Change Over Time?
The Journal of Finance, Vol. 44, No. 5, December, pp. 1115-1153.
98. Seyhun, N., 1998. Investment intelligence from insider trading, MIT Press.
99. Sharpe, S., 2002. Reexamining Stock Valuation and Inflation: The Implications
of Analysts’ Earnings Forecasts, the Review of Economics and Statistics, 84:4,
632-48.
100. Shiller, R. J., 1988. Causes of changing financial market volatility. In
Financial market volatility. The Federal Reserve Bank of Kansas City, pp1–22.
81
101. Shiller, R. J. and Beltratti, A. E., 1992. Stock prices and bond yields: Can
the comovements be explained in terms of present value models? Journal of
Monetary Economics, 30, 25–46.
102. Sowell, M., 1999. The Quest for Cosmetic Justice. [Online]. Avaialable
from: http://brothersjudd.com/index.cfm/fuseaction/reviews.detail/book_id/
746/Quest%20for%20Co.htm [Accessed 10th January 2011]
103. Spiro, P. S., 1990. The Impact of Interest Rate Changes on Stock Prices
Volatility", Journal of Portfolio Management, 16 (2), 63-68.
104. Spyrou, I. S., 2001. Stock returns and inflation: evidence from an
emerging market. Applied Economics Letters, 8, 447-450.
105. Stiglitz, J. E. and Weiss, A., 1981. Credit rationing in markets with
imperfect, American Economic Review, Vol. 71, No. 3.
106. Summers, L., 1983, .The Non-Adjustment of Nominal Interest Rates: A
Study of the Fisher Effect, in J. Tobin (ed.), Macroeconomics, Prices and
Quantities, Brookings Institution.
107. Sykes, A.O., 1992. An Introduction to Regression Analysis: The Inaugural
Coase Lecture. [Online]. Available from:
http://www.law.uchicago.edu/files/files/20.Sykes_.Regression_0.pdf [Accessed
4th February 2011]
108. Taylor, M.P. and Tonks, I., 1989. The Internationalization of Stock
Markets and the Abolition of UK Exchange Control, Review of Economics and
Statistics, 71, pp.332–36.
82
109. Uddin, M. G. S. and Alam, M. M., 2007. The Impacts of Interest Rate on
Stock Market: Empirical Evidence from Dhaka Stock Exchange. South Asian
Journal of Management and Sciences, 1(2), 123-132.
110. Ulmer, J. T. and Wilson, M. S., 2003. The potential contributions of
quantitative research to symbolic interactionism. Symbolic Interaction, 26(4),
531-552.
111. Villanueva, D., 1988. Issues in Financial Sector Reform, Finance and
Development, IMF and World Bank, March.
112. World Bank, 1994. Adjustments in Africa; Reforms, Results, and the Road
Ahead, A World Bank Policy Research Report, Oxford University Press.
113. Yucel, T. and Kurt, G., 2003. Foreign Exchange Rate Sensitivity and
Stock Price: Estimating Economic Exposure of Turkish Firms, European Trade
Study Group, Madrid
114. Zhou, C., 1996. Stock Market Fluctuations and the Term Structure. Board
of Governors of the Federal Reserve System, Finance and Economics Discussion
Series Issue 96/03.
115. Zion, U. B., Spiegel, U. and Yagil, J., 1993. Inflation, investment
decisions and the fisher effect. International Review of Economics and Finance,
2, 195–206.
83
Appendices
Appendix A- List of figures
Figure 1.1: Sector representation of S&P500 index
3.75%3.44% 9.23%
9.52,%
11.68%
19.82%
11.64%
11.51,%
16.18% 3.23%
Sector Representation in Percentages
Telecom Svc UtilitiesCons Disc Cons StaplesEnergy FinancialsHealth Care IndustrialsInfor Tech Materials
84
Figure 2.1 Interest rates levels in the United States
Figure 2.2: Movements in US Treasury Constant maturity Index
Figure 2.3 US government bond yield against Inflation
(Adapted from the www.economics.troronto.ca)
85
1985 1990 1995 2000 2005 2010 20150123456789
10
year
Inte
rest
rate
s (%
)
References1. Buck, James E. (1992). The New York Stock Exchange: The First 200 Years. Greenwich
Pub. Group.2. Kent, Zachary (1990). The Story of the New York Stock Exchange. Scholastic Library Pub. I
3. Saunders, M. Lewis, P & Thornhill, A. (1997). Research Methods for Business Students.
Pitman Publishing, London.
4. Keller, G. (2005). Statistics for Management and Economics. 7th edit. Thomson,
Belmont, CA, USA.
5. Blume, E.M, 2002. Structure of the US equity market. Financial Institutions
Center [Online] Available from
6. Aggarwal, R., Ferrell, A. and Katz, J., 2007. U.S. Securities Regulation a world of
Global Exchanges. [Online] Available from
86
7. Werner F. M. De Bondt and Richard Thaler, “Does the Stock Market Overreact?” Journal of
Finance 40, no. 3 (1985): pp. 793–805.
8. Jone,M and Bacon, R., 2007. Surprise Earnings announcement: A test of market
efficiency. Proceedings of the Academy of Accounting and Financial Studies,
Volume 12, Number 1.
9. Gersdorff, N. and Bacon, F., 2007. U.S. Mergers and Acquisitions: A Test of
Market Efficiency. Journal of Finance and Accounting. Vol. 23. No.1 pp 1-5
10. Fama, E. F., 1965. “The behaviour of stock market prices”.
Journal of Business. 38:34–105
11. Sharma JL and Kennedy RE (1977) “A comparative analysis
of stock price behaviour on the Bombay, London and New York
stock exchanges”. Journal of Financial and Quantitative Analysis.
12:391–413.
12. Butler KC and Malaikah SJ (1992) “Efficiency and
inefficiency in thinly traded stock markets: Kuwait and Saudi
Arabia”. Journal of Banking and Finance. 16:97–201.
13. Thomas S (1995) An empirical characterisation of the Bombay stock exchange.
Center for Monitoring Indian Economy, University of Southern California.
14. Van den Poel Dirk, Larivière Bart (2004), Attrition Analysis for Financial Services Using
Proportional Hazard Models, European Journal of Operational Research, 157 (1), 196-
217
15. Hellum, E, 2010.What determines the developments of long term interest rates over
time? Economic Commentaries. No.3
87
16. Cheung, Y. and Ng, L 1992. Stock price dynamics and firm size. The journal of
finance. XLVII No.5 pp 1985
17. Santoni, G. and A. Tabarrok. 2002. Expected Dividend Growth, Valuation Ratios
and Rational Optimism. Journal of Financial and Economic Practice 1 (1): 110-
119.
18.Wang, Z. and Zhang, X. 2005. Empirical evaluation of asset pricing
models: arbitrage and pricing errors over contingent claims. Working
Paper, Federal Reserve Bank of New York.
88