Literature Review on Stock Market Behaviour

2.0 Introduction

The dynamic relationship between macroeconomic variables and share returns have been widely discussed and debated. It is an uneasy task to select a proper macroeconomic variable that could be most valuable in tracing the relationship between macroeconomic variables and stock market price. Besides, the findings of the literature suggest that there is a significant linkage between macroeconomic factors and stock return in countries examined. In this paper, we examine the stock price with the selected macroeconomic variables namely exchange rate, inflation rate, money supply, interest rate and industrial production in Malaysia. This part of literature review aims to contribute to the literature on the interaction between the stock market and macroeconomic variables.

In this paper, we hope that our findings would provide a deeper understating on the stock market behaviour in enhancing a better decision making for the government. Besides, it is important for us to know which macroeconomics variable would affect the stock market the most, investor would become more wise and able to proactively strategize their investment according to the change of the monetary policy (Rahman et al., 2009).

Classification of macroeconomic variable according to Economic indicator

An economic indicator is a statistic about the economy. Economic indicators allow analysis of economic performance and predictions of future performance. One application of economic indicators is the study of business cycles. Nowadays a large spectrum of macroeconomic variables is regularly published to indicate various tendencies in both private and public life ( Pilinkus.D. and Boguslauskas.V., 2009).

The leading business cycle dating committee in the United States of America is the National Bureau of Economic Research. The National Bureau of Economic Research offers a classification according to the timing how macroeconomic variables change relative to the changes of the economy as a whole (Shiskin, Moore, 1968). Economic indicators can be classified into three categories according to their usual timing in relation to the business cycle: leading indicators, lagging indicators, and coincident indicators

Leading indicators

Leading indicators are indicators that usually change before the economy as a whole changes. They are therefore useful as short-term predictors of the economy. Stock market returns are a leading indicator, the stock market usually begins to decline before the economy as a whole declines and usually begins to improve before the general economy begins to recover from a slump. Besides, money supply and inflation rate is also attributing to this group of indicators.

Lagging indicators

Lagging indicators are indicators that usually change after the economy as a whole does. Typically the lag is a few quarters of a year. The unemployment rate, interest rate and exchange rate are a lagging indicator: employment tends to increase two or three quarters after an upturn in the general economy. In a performance measuring system, profit earned by a business is a lagging indicator as it reflects a historical performance; similarly, improved customer satisfaction is the result of initiatives taken in the past.

Coincident indicators

Coincident indicators change at approximately the same time as the whole economy, thereby providing information about the current state of the economy. There are many coincident economic indicators, such as Gross Domestic Product, industrial production coincident index may be used to identify, after the fact, the dates of peaks and troughs in the business cycle

As a result, Leading macroeconomic variables dominate in scientific literature since their fluctuations set signals and help predict what the economy will be like in the future. It is relevant to state that a separate macroeconomic variable is doomed to subjectivity, thus a set of macroeconomic variables is required for a more precision picture on economic developments. (Pilinkus.D. and Boguslauskas.V., 2009).

2.1 Review of the Literature

2.1.1 Inflation rate

Inflation rate acts as a proxy for consumer price index (monthly). It is the rate at which the general level of prices for goods and services is rising, and, subsequently, purchasing power is falling. Maysami.R.C., C.H. Lee., Mohamad Atkin Hamzah. (2004), examine that the relationship between macroeconomic variables and stock market indices in Singapore pointed to a negative relation between inflation and stock prices. This result is consistent with Nadeem Sohail and Zakir Hussain (2009), Kandir. S.Y. (2008), Imran All, Kashif Ur Rehman, Ayse Kucuk Yllmaz, Muhammad Aslam Khan and Hasan (2010) which result in a rise in interest rate. Thus, this discourages investment and leads to decline in the stock prices. Besides, inflation will decrease the value of money, which ultimately effect on investments. Thus, people will tend to purchase more on durable goods, bonds, gold, foreign currency and shares, which will hedge against the inflation. ( Ahmed.R and Mustafa.K., 2000).

However, Asmy, Mohamed; Rohilina, Wisam; Hassama, Aris and Fouad, Md. (2009), for the case of Malaysia presented the result contradict with the previous researchers. The positive relationship between inflation rate and stock prices indicate that the feature of Malaysian stock prices as being good hedges against inflation.

2.1.2 Exchange rate

Exchange rate is expressed in units of the domestic currency per unit of foreign currency. Exchange rate seems to impact the stock prices positively. Imran All, Kashif Ur Rehman, Ayse Kucuk Yllmaz, Muhammad Aslam Khan and Hasan (2010) document a positive relationship between exchange rate and stock prices. This is in line with Kandir. S.Y. (2008), Nadeem Sohail and Zakir Hussain (2009), and Maysami.R.C., C.H. Lee., Mohamad Atkin Hamzah. (2004). The empirical evidence regarding the exchange rate is inconclusive.

Alsyah Abdul Rahman, Noor Zahirah Mohd Sidek and Fauziah Hanim Tafri (2009), Pilinkus.D and Boguslauskas.V (2009) investigate negative relationship between exchange rate and stock prices. The rationale behind the finding is related to the affect of exchange rate on nature of the economy. If a country is export-depending, when there is currency depreciation will lead to increase in net exports due to domestic products become cheaper relative to other countries. This result in increase in firms’ profitability will be reflected in the value of the stocks. In contrast, if a country is import-depending, currency depreciation will lead to higher import prices. Thus, it will cause a fall in firms’ profit that will be reflected in the value of stocks. (Asmy, Mohamed; Rohilina, Wisam; Hassama, Aris and Fouad, Md., 2009).

Moreover, mixed result can also be seen from Robert D.Ray, Jr., (2008) for emerging economy countries. There is positive and negative relationship between exchange rate and stock prices vary across countries.

2.1.3 Interest rate

Real interest rate which measures the purchasing power of interest receipts is calculated by adjusting the nominal rate charged to take inflation into account. The relationship between interest rate and stock prices is found to be negative. Gan.C., Lee.M.S., Au Yong.H.H., Zhang.J. (2006), Kandir. S.Y. (2008), and Alsyah Abdul Rahman, Noor Zahirah Mohd Sidek and Fauziah Hanim Tafri (2009) also report a negative relationship between interest rate and stock prices. This result is not surprising since interest rate represents alternative investments opportunities. If interest rate rises, investors tend to save more but invest less in stocks which lead to decline in stock prices. Rosylin Mohd. Yusof and M.Shabri Abd. Majid (2007) explain an increase in the interest rate reduce the stock prices and eventually the returns. Investors who seek to maximize profits tend to be more sensitive towards changes in interest rates.

Nevertheless, Nadeem Sohail and Zakir Hussain (2009) find that real interest rate has insignificant positive impact on stock prices. This result is consistent with Puah.C.H. and Jayaraman.T.K. (2007).

2.1.4 Money supply

Money supply (M2) indicates broader defined money supply in Malaysia. Some of the researchers document that there is positive relationship between money supply and stock prices. (Maysami.R.C., C.H. Lee., Mohamad Atkin Hamzah., 2004; Pilinkus.D and Boguslauskas.V., 2009; . Imran All, Kashif Ur Rehman, Ayse Kucuk Yllmaz, Muhammad Aslam Khan and Hasan, 2010; Nadeem Sohail and Zakir Hussain, 2009; Kandir. S.Y., 2008). The increase in the money supply results in the reduction in interest rate which in turn increases the stock prices On the other hand, some researchers also state that has negatively related to stock prices. (Alsyah Abdul Rahman, Noor Zahirah Mohd Sidek and Fauziah Hanim Tafri, 2009; Kandir. S.Y., 2008). A rise in the money supply will cause inflation and increase in interest rate, people tend to save more and invest less. Low investments will lead to a fall in stock prices.

Besides, Gan.C., Lee.M.S., Au Yong.H.H., Zhang.J. (2006) and Asmy, Mohamed; Rohilina, Wisam; Hassama, Aris and Fouad, Md. (2009) studies showed a mixed result between money supply and stock prices. Money supply has an immediate positive response on stock prices but that effect is dissolved and turn into negative in the long run. An increase in money supply cause higher future expected inflation hence decrease the attractiveness of stocks and stock prices in turn will fall.

2.1.5 Industrial production

Industrial production is an indicator that shows the production output from industrial activities. Nadeem Sohail and Zakir Hussain (2009), Imran All, Kashif Ur Rehman, Ayse Kucuk Yllmaz, Muhammad Aslam Khan and Hasan (2010), Humpe.A., Macmillan.P., (2009) report that stock prices are influenced positively by industrial production. This is also supported by Alsyah Abdul Rahman, Noor Zahirah Mohd Sidek and Fauziah Hanim Tafri (2009). Nevertheless, Kandir. S.Y. (2008) finds that industrial production does not appear to be significant on stock prices.

2.2 Theoretical framework

2.2.1 Rational expectation theory

Rational expectations theory defines as being identical to the optimal forecast that uses all available information. Thus, it is assumed that outcomes that are being forecast do not differ systematically from the market equilibrium results. That is, it assumes that people do not make systematic errors when predicting the future, and deviations from perfect foresight are only random. this is typically modelled by assuming that the expected value of a variable is equal to the expected value predicted by the model. The rational expectations hypothesis asserts the existence of an equilibrium, fixed point and price sequence. (Huntzinger, 1978).

P = P * + ε

P * is the rational expectation and ε is the random error term, which has an expected value of zero, and is independent of P * .

When investors expect future inflation is high, they will demand higher current incomes such as dividends to compensate the higher cost of living. To illustrate this situation, we use Gordon constant growth model:

where D1 is the next year dividend paid, k is the required rate of return of equity and g is the constant growth rate.

As we know that, high inflation means all the commodites prices will increase, which decrease our purchasing power. When investors expect future inflation rate will increase, they will require more returns, for instance dividends. If the future dividends paid by the companies remain constant, it indicates that dividends paid is lag behind the required rate of return of investors. Hence, stock price will decrease because the dividends paid, which is the returns for investors, do not keep abreast with the required rate of return of investors.

Rational expectations theory is the basis for the efficient market hypothesis. If a security’s price does not reflect all the information about it, then there exist unexploited profit opportunities, which means that someone can buy or sell the security to make a profit, thus driving the price toward equilibrium. (Sargent and Neil Wallace, 1974). In the strongest versions of these theories, where all profit opportunities have been exploited, all prices in financial markets are correct and reflect market fundamentals. Each financial investment is as good as any other, while a security’s price reflects all information about its intrinsic value.

2.2.2 Tobin’s q theory

Tobin’s q was developed by James Tobin (Tobin, 1969) as the ratio between the market value and replacement value of the same physical asset.

The Tobin’s q theory tries to relate monetary policy, which are the effects of money supply and interest rates, on the valuation of equities. If the market value reflected solely the recorded assets of a company, Tobin’s q would be 1.0. If Tobin’s q is greater than 1.0, then the market value is greater than the value of the company’s recorded assets. This suggests that the market value reflects some unmeasured or unrecorded assets of the company. High Tobin’s q values encourage companies to invest more in capital because they are worth more than the price they paid for them. Therefore, investment spending will increase because the companies can buy a lot of new investment goods with issuarance of new stocks. This can be explain as:

M ↑ >> stock price ↑ >> q ↑ >> I ↑ >> Y↑

When q is less than parity, the market seems to be saying that the deployed real assets will not earn a sufficient rate of return and thus the owners of such assets must accept a discount to the replacement value if they desire to sell their assets in the market. Furthermore, when market-wide q is less than parity, investors are probably being overly pessimistic about future asset returns.

2.2.3 Capital asset pricing model (CAPM)

Capital asset pricing model (CAPM) is used to determine a theoretically appropriate required rate of return of an asset, if that asset is to be added to an already well-diversified portfolio, given that asset’s non-diversifiable risk. The model takes into account the asset’s sensitivity to non-diversifiable risk (also known as systematic risk or market risk), often represented by the quantity beta (β) in the financial industry, as well as the expected return of the market and the expected return of a theoretical risk-free asset. The model was introduced by Jack Treynor (1962), William Sharpe (1964),  and Jan Mossin (1966). CAPM explains the magnitude of an asset’s risk premium, which is the difference between the asset’s expected return and the risk-free-interest rate.

E(Ri) = rf + βi [E(Rm) – rf]

Where E(Ri) measures the expected return on the i th asset; E(Rm) is the expected return on the market’s entire collection of financial assets; βi is a measure of an individual asset’s or portfolio of asset’s risk exposure to the measure of the whole market; and rf is the risk-free interest rate (often approximated by government treasury bills).

The risk-free interest rate element can be influenced by the changes in money supply and thus affecting the expected return of a financial asset. Hence, volatilities in monetary policy variables, may also affect the volatility in the expected return of a financial asset (Rosylin and M. Shabri, 2007).

Besides, CAPM model has also proved to be useful theory in terms of explaining the source of systematic risk. As we know that, βi the sensitivity of the security towards market changes. If βi is greater than 1, it indicates that the security is very sensitive to the market changes because market changes by 1%, the security will change by more than 1%. Market changes usually are influenced by monetary policy which is consisting money supply (M2), interest rate (Treasury bill rates), exchange rate (MYR), real output (industrial production index) and inflation rate.

2.2.4 Arbitrage pricing theory (APT)

The Arbitrage Pricing Theory (APT) holds that the expected return of a financial asset can be modeled as a linear function of various macro-economic factors or theoretical market indices, where sensitivity to changes in each factor is represented by a factor-specific beta coefficient. (Ross 1976). The model-derived rate of return will then be used to price the asset correctly, where the asset price should equal the expected end of period price discounted at the rate implied by model. If the price diverges, arbitrage should bring it back into line. APT starts with specific assumptions on the distribution of asset returns and relies on approximate arbitrage arguments. In particular, APT assumes a factor model of asset returns. Common factors driving asset returns may include GNP, interest rates and inflation.

The APT is a substitute for the Capital Asset Pricing Model (CAPM) in that both assert a linear relation between assets’ expected returns and their covariance with other random variables. (Huberman and Wang, 2005). In the CAPM, the covariance is with the market portfolio’s return. The covariance is interpreted as a measure of risk that investors cannot avoid by diversification. The slope coefficient in the linear relation between the expected returns and the covariance is interpreted as a risk premium. The APT lends itself to various practical applications due to its simplicity and flexibility which are asset allocation, the computation of the cost of capital, and the performance evaluation of managed funds.

2.2.5 Wealth effect

Wealth effect is an increase in spending that accompanies an increase in perceived wealth. The effect would cause changes in the amounts and distribution of consumer consumption caused by changes in consumer wealth. People can use some of their disposable income to invest in assets instead of consuming. (Poterba, 2000).

Disposable incomes = Consumptions + Investments

According to the life cycle model, households accumulate and deplete their wealth to keep their planned consumption spending steady, even when their income is expected to fall as it might during retirement. In the absence of wealth surprises, the life cycle model predicts that wealth could vary substantially over time but that consumption spending will be relatively stable. However, if households experience an unexpected increase in their wealth, then households will formulate a new spending plan that involves a higher level of outlays indefinitely into the future. Therefore, the life cycle model suggests that predictable changes in household income and wealth, such as those reflecting new investments deliberately generated by thrift, should not lead to changes in planned spending, while household spending should respond to unexpected changes in wealth, such as from a stock-market surprise. (Davis and Palumbo, 2001).

2.2.6 Fisher effect

According to the principle of monetary neutrality, an increase in the rate of money growth raises the rate of inflation but does not affect any real variable. The Fisher hypothesis suggests that there is a positive relationship between interest rates and expected infation. (Granvillez and Mallick, 2004; Berument and Jelassi, 2002). As nominal rate of interest and rate of inflation moved one-to-one, real rate of interest thus is immune to changes.

Nominal interest rate = real interest rate + expected inflation rate

When inflation is high, it will deteriorate the real wealth of the investors. Therefore, they require higher rate of returns to compensate the rising inflation. Taking the example of bonds price, when the coupon rate is lower than the market rate, the bonds are selling at discount because of high nominal interest rate.

where p is bond price and i is nominal interest rate.

There is an inverse relationship between bond price and nominal interest rate. Hence, when investors expect future inflation will increase, nominal interest rate will increase in proportional with inflation. At that time, bonds price will decrease because investors demand for the same real return. This can be explained by followings:

M↑ >> inflation↑ >> nominal i ↑ >> bond P ↓

2.3 Hypotheses Development

Based on various theoretical and conceptual frameworks coupled with the results of previous studies, this research examines the effects of macroeconomic variables on stock prices in the emerging Malaysian stock market. In order to achieve the objective of the study, we hypothesize certain relationships between exchange rate, industrial production, inflation rate, interest rate and money supply with the Kuala Lumpur Composite Index. The following hypotheses are developed.

Exchange Rate

A depreciation of the ringgit Malaysia will lead to a rise in demand for Malaysia’s exports and consequently, increasing cash flows to the country, assuming that the demand for exports is elastic. This rise in demand will enhance the stock market level, suggesting a positive relationship between exchange rate and Malaysian stock prices. The finding is consistent with Menike (2006) and Mohammad et al. (2009), who established positive relationship between the exchange rate and stock prices in Sri Lanka and Pakistan respectively.

H0: Exchange rate is positively related to KLCI

H1: Exchange rate is negatively related to KLCI

Our null hypothesis is that exchange rate is positively related to KLCI, while the alternative hypothesis describes that the exchange rate is negatively related to KLCI. Parallel to the empirical studies, we expect that we do not reject H0, indicating that exchange rate is positively correlated to the Kuala Lumpur Composite Index.

Industrial Production

Industrial production is typically used as a proxy for the level of real economic activity, that is, a rise in industrial production would signal economic growth. Maysami et al. (2004) hypothesized a similar positive relationship through the effects of industrial production on expected future cash flows. We hypothesize likewise, noting that industrial production index is positively related to the stock prices in Malaysia. In other words, an increase in industrial production index would lead to a rise in stock exchange prices. Aisyah et al. (2009), who found a positive relationship between industrial production index and stock prices in Malaysia, further support this hypothesis.

H0: Industrial production is positively related to KLCI

H1: Industrial production is negatively related to KLCI

Null hypothesis demonstrates that industrial production is positively associated to KLCI, while alternative hypothesis is that industrial production is negatively associated to KLCI.

Inflation Rate

A rise in inflation generates a level of uncertainty, which in turn decreases the economic activity and lowers the expected output in future that finally results a decline on the stock prices. Hence, it is concluded that inflation rate is inversely related to stock prices. The suggestion is consistent with Chatrath et al. (1997) study which provided an evidence of a negative relationship between market returns and inflationary trends in India. We hypothesize similarly, signifying that there is a negative relationship between inflation rate and KLCI.

H0: Inflation rate is negatively related to KLCI

H1: Inflation rate is positively related to KLCI

Our null hypothesis is that inflation rate is positive related to KLCI, and alternative hypothesis defines the opposite if null hypothesis is not true. We do believe that our results will not allow us to reject the null hypothesis.

Interest Rate

Since most companies finance their capital equipments and inventories through borrowings, a reduction in interest rates reduces the costs of borrowing and consequently serves as an incentive for expansion. This will have a positive effect on future expected returns for the firm. Thus, stock prices react negatively to the interest rate and consistent with the findings of Menike (2006), Maysami et al. (2004) as well as Pilinkus and Boguslauskas (2009). We hypothesize the same, saying that an inverse relationship between interest rate and stock prices.

H0: Interest rate is negatively related to KLCI

H1: Interest rate is positively related to KLCI

Our null hypothesis describes that interest rate is negatively related to KLCI, while alternative hypothesis states that interest rate is positively related to KLCI. We assume our null hypothesis is true, in which we do not reject it.

Money Supply

Theoretically, the money supply has a negative impact on stock prices because, as money growth rate increases, the inflation rate is also expected to increase, and consequently the stock price should decrease. On the other hand, an increase in money supply growth would also indicate excess liquidity available for buying securities, resulting in higher security prices as well as stimulating the economy. So we have found ambiguous effects. Assuming that effects of a rise in inflation rate are minor, we hypothesize a direct relationship between money supply and stock prices, supported by Bilson et al. (2001), Menike (2006) and Gan et al. (2006).

H0: Money supply is positively related to KLCI

H1: Money supply is negatively related to KLCI

Our null hypothesis is that money supply is positively correlated to KLCI, while alternative hypothesis demonstrates that money supply is negatively correlated to KLCI. We expect that we do not reject the null hypothesis.

2.4 Conclusion

This paper examines the factors that affect the Malaysian stock prices from the macroeconomic perspective. Many studies have been taken with the different macroeconomic variables when searching for the relationship between macroeconomic factors and stock market prices. In this paper, we have chosen five of the most relevant macroeconomic variables in the investigation in Malaysia including exchange rate, inflation rate, money supply, interest rate and industrial production. Those variables indicate overall country’s economic situation and they have been chosen as a representative for stock market price fluctuation. It is an empirical question whether principal economic indicators such as exchange rate, inflation rate, money supply, interest rate and industrial production are significant explanatory factors of Malaysia stock prices. But based on our research assumption, we assume exchange rate, money supply and industrial production are positively related to the stock price. In the meanwhile, interest rate and inflation rate are assumed to be negatively related to the stock prices in Malaysia.