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In financial economics, a number of studies laid emphasis on macroeconomic factor being the causal effect of stock market movement. The stock market is a common feature of an economic growth and it is reputed to perform some necessary functions through which long-term funds of the major sector of the economy are mobilized and harnessed, which promote the growth and development of the economy. The stock market is an important factor in business investment decisions, because the price of shares affects the amount of funds that can be raised by selling stock to finance investment spending. Trends in globalization and introduction of varieties of new instruments being traded has made stock market complex. However, as economy develops, more funds are needed to boost the rapid growth of all facet of the economy. This makes stock market to serve as a tool in mobilizing and allocating of savings among competing uses which are critical to the growth and efficiency of the economy (Alile, 1997). As the stock market mobilizes savings concurrently it allocates a larger proportion of it to the firms with relatively high prospect as indicated by its rate of returns and level of risk.

Macroeconomic variables such as Money supply, Exchange rates, Interest rates, Inflation rate, Gross Domestic Product (GDP), Index of production, Unemployment etc have been identified as part of the major economic factors that affect stock returns (see for example, Chen et al., 1986, Fama, 1991, Arestis & Demetriades, 1997, Priestly, 1996, Taufiq Choudhry, 1999, Stijn Van Nieuwerburgh et al., 2005, Christopher Gan et al., 2006, Robert D. Gay, Jr., 2008, Athanasios and Antonios, 2009, e.t.c.). It is of importance to examine how these macroeconomic variables relate to stock market and their impact on expected return whilst minimizing risk. The effects of money supply cannot be over emphasized. As the economy grows stage by stage, monetary policy stimulates the economy and increases cash flow among individuals thereby making demands for financial assets point northbound. Stock prices increases as soon as the demands are translated to bid/ask market.

The Bank of England core purposes is to promote economic growth by maintaining price stability and supporting Government's economic policies. The Bank of England performs its monetary stability function in other to ensure stable prices, low inflation and sustainable confidence in the currency. Monetary policy operates in the UK through influencing the price of money (adjustment of base rate - interest rate). In March 2009, the instrument of monetary policy shift towards the quantity of money provided as a result of the quantitative easing.

Source: Bank of England

Money appears to be a major influence on inflation, business cycles and interest rates. The relation between money and prices is historically associated with the quantity theory of money. There is strong empirical evidence of a direct relation between inflation and money supply growth. A country such as Zimbabwe which saw rapid increases in its money supply also saw rapid increases in prices. This is one of the reasons why monetary policy serves as a means of controlling inflation in the United States of America. Dhakal et al. (1993) suggested that money supply changes affect stock prices indirectly through their effects on real activity. Chong and Goh (2003) examine macroeconomic variables such as money supply and interest rate and re-affirmed the efficient market hypothesis (EMH). EMH suggest that competition among the profit-maximizing investors in an efficient market will ensure that all the relevant information currently known about changes in macroeconomic variables are fully reflected in current stock returns, so that investors will not be able to earn abnormal profit through prediction of the future stock market movements. Schwert (1981) results contradict the efficient market hypothesis. Schwert examines the stock market reaction to the monthly CPI inflation rate announcement and does use a measure of unexpected inflation rather than just the announcement rate.

Chart 2: Price Inflation - CPI, RPI and RPIX (Percentage changes over 12 months)

Source: Office for National Statistics

The CPI is the main UK measure of inflation for macroeconomic purposes and forms the basis for the Government's inflation target. High rate of inflation is linked to the excessive growth of money supply. But low or moderate rates of inflation are more varied as there are no sustainable factors being determined. However, low or moderate inflation may be attributed to fluctuations in real demand and supply for goods and services as well as to growth in money supply which in turn lower the demand for stocks and assets. More views are on the opinion that a long sustained period of inflation is caused by money supply. Lee and Wong (2005) estimated the threshold levels of inflation for Taiwan and Japan using quarterly data set from the period between 1965- 2002 for Taiwan and 1970-2001 for Japan. Their estimation of the threshold models suggest that an inflation rate beyond 7.25% detrimental for the economic growth of Taiwan. On the other hand, they found two threshold levels for Japan, which are 2.52% and 9.66%. They argue that rate of inflation is positively related to money growth and the rising interest rates and inflation affect corporate earnings leading to lower stock returns. The findings of Lee (1992) supported the findings of Najand and Rahman (1991) and Shcwert (1989) in that there is strong evidence of the causal relationship that exist between inflation and stock returns.

The Bank of England sets interest rates to keep inflation low, issues banknotes and works to maintain a stable financial system. Interest rate stability is desirable because fluctuations in interest rates can create uncertainty in the economy and make it harder to plan for the future. The extent of interest rate in determining the stock return movement has been studied. It is widely accepted that increase in interest rate would increase the required rate of return and share price would decrease with increase in the interest rate (see Gan et al., 2006). The relationship between stock returns and nominal interest rates reflects the ability of an investor to change the structure of her portfolio (Apergis and Eleftheriou, 2002). French et al. (1987) responded negative relationship existence between stock return and interest rate. Bulmash and Trivoli (1991) studied US stock market in relation to money supply and Treasury bill rate. They found negative relationship between stock returns and Treasury bill rate but positive relationship between stock returns and money supply. Islam and Watanapalachaikul (2003) examined Thailand economy between the period of 1992 to 2001. They argue that interest rate, bonds price, foreign exchange rate, price-earning ratio, market capitalization and consumer price index show a significant long-run relationship with stock returns.

Although the precise cause and effect relationship between economic variables and stock returns is unknown, they are believed to be related. The link between stock market performance and economic growth has been studied among analysts with a reference on both developed and emerging markets. Geske and Roll (1983) and Kaul (1987) emphasize the importance of policy responses in explaining stock returns. Shiller (1988) reflects on changes in investor's expectations as regards asset pricing in relation to certain economic variables. Chong and Goh (2005) emphasize the importance of macroeconomic variables as relating to investors earning abnormal profit returns. It is widely accepted that Stock market returns shows an efficient market hypothesis (EMH). EMH is currently defined in three forms (Fama, 1991). Firstly, the weak form holds that the current price reflect the information contained in the record of past price. Secondly, the semi-strong form holds that prices reflect not just past prices but all other published information. Thirdly, strong form holds that prices reflect all information both that published as well as that not yet published (insider information). Fama (1991) argues that stock returns do not show a strong form nor weak form but rather semi-strong form efficiency. This means that stock price movement must reflect all publicly available information and not fundamental or technical analysis about the security. Athanasios and Antonios (2009) are of the same view with Fama's hypothesis affirming that the negative relationship between stock returns and inflation reflects positive impact of real variables on stock returns. It is expected that efficient stock market is to reflect available information on monetary growth rates and interest rates.

It is a general believe that stock returns are determined by some fundamental macroeconomic variables such as interest rate, exchange rate and inflation rates, GDP, index of production etc. Both empirical and theoretical literatures have attempted to capture the effect of economic forces on stock returns in different countries. Ross (1976), Chen et al. (1986) developed the Arbitrage Pricing Theory (APT), and used the theory to examine the US equity market. They used some macroeconomic variables to explain stock returns in the US stock markets. The authors' findings showed both anticipated and unanticipated inflation rates to be negatively correlated to the expected returns. But industrial production, changes in risk premiums, and changes in the term structure were positively related to the expected stock returns.

However, stock markets play an important role in stimulating economic growth. Our study is to examine the relationship of interest rate, inflation rate, money supply on FTSE 100 index. The FTSE 100 index comprises mid-capitalized companies and represents approximately 15% of UK market capitalization. Companies in FTSE 100 are selected quarterly as being the 101st to 350th largest companies with their primary listing on the exchange.


The relationship between economic growth and stock market has been the subject of intensive theoretical and empirical studies (James Laurenceson, 2002). The question is whether stock market development causes economic growth or reversely.

A great deal of research has been conducted in the developed market (US, UK, Australia, Belgium, France etc) and in emerging markets (India, Nigeria, Russia etc) as regards the relationships between macroeconomic variables and stock market returns.

Hashemzadeh and Taylor (2007) examined the relationship and direction of causality between Money supply and Stock price, and Interest rate and Stock price using weekly data from 2nd January 1980 to 4th July 1986 for Standard & Poor's 500 Stock Index. They concluded that bi-directional causality is present in regression models which relate Stock prices to Money supply and vice versa. However, their result for relationship between Stock prices and Interest rate was not conclusive.

Nil Günsel and Sadik Çukur (2007) examined the effect of macroeconomic variables on London Stock Returns using OLS technique to investigate the performance of Arbitrage Pricing Theory (APT) in London Stock Exchange for monthly period covering 1980-1993. They found out that macroeconomic factors have a significant effect in the UK stock exchange market.

Also, in the emerging markets, Osinubi (1998) examined the case of Nigerian Stock Exchange and came out with a conclusion that there is a positive relationship between growth and all the stock market development variables.

The main objective of this study is to empirically examine some peculiarities or differences that exist between selected macroeconomic variables and stock market index, a case study of London Stock Exchange FTSE 100 Index using regression analysis. Knowledge of the effect of selected macroeconomic variables on stock returns would enhance portfolio and investment risk management and subsequently increase investor's confidence in stock market and enhance the adequacy of corporate resource allocation.


With the understanding that stock market provides funding for economic growth, my empirical studies will extend on previous studies and focus on the effect of selected macroeconomic variables (Inflation rate, Interest rate and Money supply) on Stock return. I will investigate the possible relationship that exist between selected macroeconomic variables and Stock returns (LSE FTSE 100 Index) using granger causality and multiple regression method of analysis on monthly secondary data covering the period April 2005 to March 2010.


The following research question will form the core of empirical investigation of this study.

Does, Inflation rate, Interest rate, and Money supply affect Stock returns using London Stock Exchange (FTSE 100 Index)? If, yes to what extent? This will be proved or shown empirically by conducting correlation and multiple regression analysis.

I would like to know the direction of causality between Inflation rate, Interest rate, Money supply and Stock returns with the use of Granger Causality test i.e. testing to know if one variable predicts the other variable.


This study is organised as follows. The next section presents review of relevant literature while section three covers the methodology, data and sample selection procedure used in the research work. Data was presented and analysed in section four and the final section contains summary of results and conclusion based on findings.

Chapter 2

Literature Review



The Capital Market is a market for securities where long term funds are raised and includes the stock and bond market. The Capital Market is divided into two: the primary market; and the secondary market. The primary market is the market for initial offering of stocks or debts while the secondary market provides a window for subsequent trading in existing stocks. The Stock Market is used to refer to all the stock exchange markets. The Stock Exchange is an entity where stocks and securities are listed for traders to buy or sell. The entity also provides facilities for the issue and redemption of securities and other financial instruments.


According to Michie (1999), the London Stock Exchange represented a central position within the British financial system as both a market and an institution. The London Stock Exchange is the most international of the world's stock exchange with around 3,000 companies from over 70 countries admitted to trading on its markets. It is an organised market for securities. Securities traded on LSE includes UK and international equities, debt, covered warrants, exchange traded funds (ETFs), Exchange Traded Commodities (ETCs), Reits, fixed interest, contracts for difference (CFDs) and depositary receipts.


The concern of the role of stock market in economic growth has been studied both theoretically and empirically by Chen et al. (1986), Poon and Taylor (1991), Thornton (1993), Taufiq Choudhry (2001), Christopher Gan et al. (2006), Robert D. Gay, Jr. (2008), and Athanasios and Antonios (2009). The stock market is perceived as an indicator to mirror the economy through which long-term funds mobilization are provided (Inanga and Emenuga, 1997), harnessed and made available to various sectors of the economy (Nyong, 1997). The stock market is classified by economist as a tool for business direction and affects policies of the economy.

Stock markets may affect economic activity through liquidity. Liquid stock markets make investment less risky and more attractive to investors. By doing so, stock market liquidity can also lead to more investment. Empirical evidence strongly supports the view that liquidity boosts economic growth (Levine, 1991, Greenwood and Smith, 1996, Nil Günsel and Sadõk Çukur, 2007) but according to Bencivenga et al. (1996), without liquid capital market there would not be industrial revolution.

Stock market is one of the most important sources of generating liquidity for companies and individual. History has shown that the price of shares is an important part of the dynamics of economic activity which often referred to as primary indicator of a country's economic strength and development. Notable among the functions of the stock market are risk diversification, savings, and liquidity creation among others.

The inter-relationship that coexists between stock market and economic growth vary in different economy due to their level of development (Filler et al., 1999). The work of Demirguc-Kunt and Levine (1996) shed more light on effect of the function of stock markets on economic growth. They argue that increasing return on investment through income inhibit savings rate. As savings rate falls and with the existence of externality attached to capital accumulation, greater stock market liquidity could slow down economic growth. Edo (1995) asserts that securities investment is a veritable medium of transforming savings into economic growth and development and that a notable feature of economic development in Nigeria since independence is the expansion of the stock market thereby facilitating the trading in stock and shares.

Levine and Zervos (1996) examines whether there is a strong empirical association between stock market development and long-run economic growth using data of 49 countries between the periods 1976 to 1993. They investigated whether measures of stock market liquidity, size, volatility, and integration in world capital markets predict future rates of economic growth, capital accumulation, productivity improvements, and private savings. Their findings suggested that financial markets and institutions provide important services for long-run growth, and stock markets and banks future rates of economic growth.

However, effort was also made by Nieuwerburgh et al. (2005) with the view of "Institutional changes affecting the stock exchange explain the time-varying nature of the link between stock market development and economic growth". They studied to what extent macroeconomic factors could affect stock market changes in Belgium for a period between 1873 and 1935 using Granger Causality tests. They found strong evidence that stock market development caused economic growth in Belgium especially during the test period.

Athanasios and Antonios (2009) used four different approaches to examine the causal relationship between stock market development and economic growth, a case study of France for the period 1965-2007. The methods are (1) unit root test: to examine stationary (2) Johansen co-integration analysis: to examine whether the variables are co-integrated of the same order (3) A vector error correction: to investigate the long-run relationship between stock market development and economic growth (4) Granger causality: to examine the direction of causality between the examined variables of the estimated model. They concluded that "A short-run increase economic growth of per 1% leaded to an increase of stock market index per 0.24% in France, while an increase of interest rate per 1% leaded to a decrease of stock market index per 0.64% in France".


The link between stock market returns and key economic variables in developed and emerging market is well documented. The link can be attributed to research of Chen et al. (1986), Hashemzadeh & Taylor (1988), Levine and Zervos (1996), Priestly (1996), Arestis & Demetriades (1997), Taufiq Choudhry (1999), Stijn Van Nieuwerburgh et al. (2005), Christopher Gan et al. (2006), Robert D. Gay, Jr (2008), and Athanasios & Antonios (2009), in which their studies identified the relationship between stock market returns and macroeconomic factors in terms of production rates, productivity, GDP growth rate, unemployment, inflation rate, exchange rate, interest rate, money supply, etc.

Chen, Roll and Ross (1986) investigated the sensitivity of seven macroeconomic variables on United States stock market returns and their influence on asset pricing between 1958 and 1984. The seven macroeconomic variables were term structure, industrial production, risk premia, inflation, market indices, consumption, and oil prices. Using the efficient-market theory, rational expectations and inter-temporal asset-pricing theory, they established that the economic state variables work as discount rate and affect the future dividends, which in turn influence the stock values and concluded that asset prices should depend on exposures to the state variables that describe the economy. Their conclusion was consistent with the asset-pricing theories of Merton (1973), Cox et al (1985) and the APT of Ross (1976).

Hashemzadeh & Taylor (1988) applied the definition of causality proposed by Granger (1969) and further developed by Sims (1972) to investigate the empirical relationship between stock price and money supply, and stock price and interest rate. Using weekly data weekly data for Standard and Poor's 500 Index from 2nd January 1980 to 4th July 1986, they concluded that bi-directional causality is present in regression models which relate stock prices to money supply and vice versa. However, their results were not conclusive with respect to the relationship between stock prices and interest rate as the causality seems to be mostly running from interest rates to stock prices, and not the other way round. This empirical analysis follows the work of Hashemzadeh & Taylor (1988) in studying the UK market as against the US market. Also, three macroeconomic variables were analysed by adding Inflation rate (interest rate, money supply and inflation rate) instead of two macroeconomic variables.

Priestley (1996) suggested the factors that may carry a risk premium in the UK stock market with seven macroeconomic and financial factors (default risk, industrial production, exchange rate, retail sales, money supply unexpected inflation, change in expected inflation, term structure of interest rates, commodity prices and market portfolio). He collected Stock prices data on 69 randomly selected United Kingdom companies for the period December 1979 to August 1993. He concluded that the APT model with Kalman-filter innovations performs best; both in-sample and out-of-sample and those firms wishing to use a risk-adjusted measure of the cost of capital should first employ the APT rather than the CAPM since it offers a richer description of the return generating process.

Also, Flannery and Propapadakis (2002) stated that macroeconomic variables are excellent candidates for these extra market risk factors, because macro changes simultaneously affect many firms' cash flows and may influence the risk-adjusted discount rate. Economic conditions may also influence the number and types of real investment opportunities. Moreover, Yasaswy (1994) states, "to gain an insight into the complexities of the stock, one needs to develop a sound economic understanding and be able to interpret the impact of important economic indicators on stock prices"

Christopher Gan et al. (2006) examined whether the New Zealand Stock Index(NZSE40) is cointegrated with a group of macroeconomic variables (the inflation rate, long term interest rate, short term interest rate , exchange rate index , GDP, money supply (M1) and domestic retail oil prices) in the long run. They affirmed that the NZSE40 is majorly determined by the interest rate, money supply and real GDP and no strong evidence for the stock market index to be a leading indicator for changes in macroeconomic variables.

Gunsel and Cukur (2007) extended the approach of Chen, Roll and Ross (1986) by investigating the performance of the Arbitrage Pricing Theory (APT) in London Stock Exchange using ordinary least square (OLS) technique on monthly data for the period of 1980 to 1993. They considered seven macroeconomic variables which are: the term structure of interest rate; the risk premium; exchange rate; money supply; unanticipated inflation rate; sectoral dividend yield; and sectoral unexpected production. They used a total of 87 firms to form industry portfolio and concluded that macroeconomic factors have a significant effect in the UK stock exchange market, and that each factor may affect different industry in different manner. The macroeconomic variables are correlated but are quite low. Also, the correlation for the industry was a different direction as they showed high correlation. Regression results among the industry portfolio against macroeconomic variables showed R2 varies from 94% to 28%. Their results show that the industry of Building Materials & Merchants and Engineering suffer because of exchange rate movements, and the Chemical industry is positively affected by exchange rate movements. Industrial production have negative relationship with Paper, Packaging & Printing, Food, Beverage & Tobacco, and Engineering industries, and a positive relationship with Households, Goods & Textiles industries. In finding relationship with risk premium, they discovered only one month lag risk premium of construction industry has a negative effect with stock return. As regards money supply, out of five industries investigated, three were positively affected while others were negatively correlated with money supply. They also show that only one month lag term structure of interest rate has positive effect for some of the industries while two month lag term structure has a very small negative effect on industry returns.


According to Geske and Roll (1983), stock returns are negatively related to both expected and unexpected inflation contrary to economic theory and common sense. They argued that this puzzling empirical phenomenon does not indicate causality. They also argued that the negative relationship between stock returns unanticipated inflation are really two ways to measure the same thing.

They offered a supplementary argument based on the following: a random negative (positive) real shock affects stock returns which, in turn, signal higher (lower) unemployment and lower (higher) corporate earnings. This leads to lower (higher) personal and corporate tax revenues. Government expenditures do not change to accommodate the change in revenues so the Treasury's deficit increases (decreases). The Treasury responds by increasing (decreasing) borrowing from the public. The Federal Reserve System purchases some of the change in Treasury debt and eventually pays for it by expanding (contracting) the growth rate of base money. Higher (lower) inflation is induced by the altered money base growth rate. Since rational investors realize that a random real shock signaled by the stock market will trigger this chain of fiscal and monetary responses, they alter the prices of short-term securities contemporaneously with the stock return signal. To the extent that an increased (decreased) deficit, triggered by a real shock, is not expected to be "monetized" by the Federal Reserve, the Treasury's increased (decreased) supply of debt securities can also cause an increase (decrease) in real interest rates. Thus, Investors decide collectively on whether a particular stock return signifies a change in real rates, in expected inflation rates, or in both.

Taufiq Choudhry (2001) investigated how stock market in four high inflation countries reacts to inflationary pressure. The countries he investigated were Argentina, Mexico, Venezuela and Chile during the 80s and 90s. The results show that past and present inflation has relationship with the current stock returns and there is inverse relationship with one-period lagged inflation.

Saryal (2007) used Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model to estimate the impact of inflation (Consumer Price Index) on conditional stock market volatility using monthly data from Turkey (Turkish Stock Market - ISE100 Index) between January 1986 to September 2005 and Canada (Canadian Stock Market - TSE 300 Index) between January 1961 to December 2005. He concluded that Inflation rate has high predictive power for stock market volatility in Turkey with a weaker but significant effect for Canada. He also observed that the higher the Inflation rate, the greater the stock market volatility.


Chawla and Srinivasan (1980) in their study of the relationship between returns on security, money supply and interest rate found that money supply and interest rate bear correct and significant relation in explaining the variations in security prices. Two factors jointly explained 35% of total variations in security prices.

Flannery and James (1984) examined the effect of interest rate changes on common stock returns of financial institutions and concluded that interest rates were found to be significantly related to stock price movements for commercial bank and Savings &Loans stocks. Cross-sectional variation in the interest rate sensitivity measure is significantly related to the maturity mismatch of the banks' assets and liabilities. This is consistent with the nominal contracting hypothesis, i.e. the maturity composition of nominal contracts is found to be a significant factor affecting common stock returns.

Darrat (1990) used the FPE/multi-variance Granger-causality modelling technique to test whether changes in Canadian stock returns were caused by a number of economic variables using monthly data from the Canadian Stock Exchange covering January 1972 through February 1987. His Empirical results revealed that when the volatility of interest rates begins to rise, investors would want to shift out of bonds and into equities, exerting upward pressure on stock returns. However, a persistent rise in interest volatility could be interpreted as a rise in the overall economic uncertainty. This would, in turn, raise the risk premium attached to stocks, leading to a fall in stock returns.


Ho (1983) used cointegration and causality test to investigate the effect of money supply (M2 and M1) on stock return. He examined Australia, Hong Kong, Japan, Philippines, Singapore and Thailand markets for the period 1975 to 1980 using monthly data and concluded that only Japan and Philippines markets exhibit unidirectional causal relationship between the money supply measurement (M1 and M2) and stock return. For other countries, Hong Kong, Australia, Singapore and Thailand, stock markets only relates to M2.

Pearce and Roley (1983) investigated the response of stock return to weekly money announcements using United States weekly data from 29 September 1977 to 29 January 1982. They asserted that stock returns respond only to the unanticipated change in the money supply as predicted by the efficient markets hypothesis. They further argued that an unanticipated increase in the announced money supply depresses stock returns while an unanticipated decrease elevates stock returns. They also added that the stock return response does not depend on the relationship of the money supply to the long run and the stock return response is essentially complete early in the subsequent trading day.

In a later study, Pearce and Roley (1985) again examined the daily response of stock prices to announcements of the narrowly defined money stock, the consumer price index, the producer price index, the unemployment rate, industrial production and the Federal Reserve's discount rate. Except for the discount rate, survey data on market participant's expectations of these announcements were used to identify the unexpected component of the announcement in order to test the efficient market hypothesis that only the unexpected part of any announcement, the surprise, moves stock prices. The empirical results supported this hypothesis and indicated further that surprises related to monetary policy significantly affect stock returns.

2.5 Country Specific

Despite that different economic variables influence stock return in different stock markets, the macroeconomic variables that influence stock return in various economies are not the same; the variables as a matter of fact fall under the same economic factors.

Poon and Taylor (1991) reflect their study on the United Kingdom stock market using ARIMA model on monthly and annual growth rate of risk premium, term structure, industrial production and value weighted market index. It was affirmed that macroeconomic variables strongly affect stock returns in USA than in UK. They suggest that the model used for testing the APT cannot be used for making prediction in UK stock market and further concluded that the explanatory power of APT in pricing UK stock is not high. Their findings were related to Chen, Roll and Ross (1986) and reemphasize the importance of representing only the unexpected component of share returns and macroeconomic variables.

Cheng (1995) examine UK stock market with a different approach but with same findings. He uses canonical correlation method to analyse the linkage between the factor scores of the set of security returns and those of the set of economic indicators between January 1965 and December 1988 inclusive. He cross examine 61 securities in UK stock market and found that the security returns are positively related to the longer leading indicator: money supply (M1); government securities price index; and unemployment rate respectively. He also observed a very small negative correlation between the security returns, referred to as the lagging indicator, and interest rate.

A study on Canada, Germany, Italy, Japan and US by Cheung and Ng (1998) with quarterly data examine long term co-movements between the national stock index and macroeconomic variables (such as real oil price, real consumption, real GNP and money supply). They conclude that there are long term co-movements between the national stock index and the macroeconomic variables used.

In a similar context, Arestis & Demetriades (1997) concluded that the relationship between stock markets returns and macroeconomic variables in the US was largely positive but insignificant in the case of Germany.

Robert D. Gay, Jr (2008) investigated the Brazil, Russia, India and China (BRIC) stock market and the linkage with two macroeconomic variables (exchange rate and oil price). It was evidenced that there exist relationship between exchange rates and stock prices for Brazil, India, and China but not for Russia. The other economic variable, oil price do not show a significant relationship between the three stock market exchanges.

2.6 Method Used to Examine Relationship between Macroeconomic Variables and Stock Return

Granger (1981) introduced the existence of a long-run relationship between non-stationary variables and the concept of "co-integration". Granger further developed what he introduced in 1987. Stock (1987) has shown that the regression between two non-stationary series yt and xt would produce highly consistent as well as efficient estimates of the parameters, if they were co-integrated. Thus co-integration tests are important in determining the presence and nature of an equilibrium relation. In addition, if two or more non-stationary time series share a common trend, then they are likely to be co-integrated.

Kwon and Shin (1999) examine Korean stock market by applying Engle-Granger cointegration and the Granger-causality tests from the Vector Error Correction Model (VECM). They investigate whether economic activities (exchange rate, money supply, trade balance and production index) in Korea can explain stock market returns. They conclude that Korean stock index is not a leading indicator for economic variables.

Johansen cointegration test in the Vector Error Correction Model (VECM) provided another approach to investigate whether stock market index cointegrate with macroeconomic variables as reflected in studies carried out by Mukherjee and Naka (1995) and Mayasmai and Koh, (2000). Mukherjee and Naka (1995) studied Japanese stock market in finding evidence if the stock market index cointegrates with six macroeconomic variables (money supply, exchange rate, production index, inflation rate, long term government bond rate and short term call money rate). They concluded that there exists cointegration among the variables used. Mayasmai and Koh (2000) supported their evidence by testing Singapore stock market with five macroeconomic variables.

A study by Robert D. Gay, Jr (2008) applied the Box-Jenkins ARIMA model to investigate the time-series relationship between stock market index prices and the macroeconomic variables of exchange rate and oil price for Brazil, Russia, India and China (BRIC). The author discovered that there is no significant relationship between the macroeconomic variables and the stock market index prices for either BRIC country.