Volatility of Macroeconomic Variables that create Variation in Stock Returns

Literature review is an analysis or summary of previous researches towards a particular topic. The purpose of performing literature review is to evaluate related literature in order to guide and support the current writing, and to define each variable involved in this study. The focus area of this study is to examine the volatility of macroeconomic variable that creates the variation in stock returns is the same for industry and firm.

It is evident from literature that the relationships between macroeconomic variables and stock returns have received big focus over recent years in specific countries and economic conditions. The amount of return achieved or expected from an investment is contingent on a variety of factors. In this study, the focus area of the macroeconomic variable will be inflation rate, exchange rate, interest rate and GDP which proxy by the industrial production index.

Butt et al., (2009) with observation 32 firms’ top performers at KSE 100 Index from Banking Industry and Textile Industry, data obtained from July 1998 until June 2008, 120 months with employ Multi Factor Method to explore the relationship between the market index, consumer price index (CPI), risk free rate of return (RFR), exchange rate (Exrate), industrial production index (IPI), money supply (M2) and individual industrial production. As the result, they found that the stock returns act different at the level in firm and industry. The impact of changes in economic factors on the stock returns was showed more significant in the level of industry than the level of firm level. They concluded that the stock returns of industry were subjected to larger variation against macroeconomic variables that the stock returns of firm level.

Bredin, Hyde, and O’Reilly, (2009) had showed that financial and macroeconomic factors influence on the stock returns respond in a nonlinear fashion. The world stock returns had captured the non-linearity or cyclical behavior with the large negative falls leading to a different regime to that of smaller negative or positive returns. These single evolution models all segregate extreme falls in return or in the crisis period such as October 1987the consequence of the Asian financial crisis and the impact of the 9/11 terrorist attacks in September 2001. Study from Longin and Solnik (2001) and Ang, Chen and Xing (2006) had showed that covariance between country stock return and world stock returns increases during these periods.

2.2 THE MACROECONOMIC VARIABLES THAT INFLUENCE STOCK PRICE

2.2.1. Relationship between inflation rates and stock returns

Wang (2010) inspected on the effect of inflation, interest rate, and GDP on China’s Stock Market (Shanghai Composite Index) by use exponential generalized autoregressive conditional heteroskedasticity (EGARCH) and lag-augmented VAR (LA-VAR). Data started from January 1992 to December 2008 by month report stock price index from China Economic Information Network. He also proved that there is a mutual causal relationship between stock market and inflation volatility. This has been proven from the existence of a feedback incident between China’s CPI and stock prices.

Through the data collect from Turkish Central Bank from January 1981 to December 2000, Sari and Soytas, (2005) had showed the expected inflation and real returns are not related, but there was negative relationship between the inflation and the stock returns. This negative relationship comes into sight to be stemming from the negative impact of unexpected inflation on real stock returns. Therefore, they test the validity of the proxy explanation for the negative relationship between inflation and real returns. The result provided weak support for this test and he concluded that Turkish stocks do not appear to be a perfect hedge against inflation.

Maysami and Sims (2002, 2001a, 2001b) had examined the relationship between macroeconomic variables and stock returns in Hong Kong and Singapore, Malaysia and Thailand and Japan and Korea. They employed Hendry’s (1986) Error-Correction Modeling technique to predict the short-run and long run relationship between macroeconomic variable which include interest rate, inflation, money supply, exchange rate and real activity, along with a dummy variable to capture the impact of the 1997 Asian financial crisis. They found that the influence of these macroeconomic variable on each 6 countries stock market index were different depending on the particular country’s financial structure.

With use Johansen’s (1998) VECM to investigate the relationship between Japanese Stock Market and macroeconomic variables include exchange rate, inflation, money supply, real economic activity, long-term government bond rate, and call money rate; Mukherjee and Naka (1995) had found out that the significant relationship between the movement of Japanese Stock Market and these macroeconomic variables.

Similarly, Maysami and Koh (2000) conduct the research on relationship between macroeconomic variable such as inflation, money supply growth, changes in short term and long term interest rate and exchange rate; and Singapore’s stock market. They found that a co-integrating relation between the macroeconomic variables and the changes in Singapore’s stock market levels.

With employed CPI, IIP, money supply and foreign exchange rate as dependents variable, Nishat and Shaheen (2004) had claim that different variable has different result against the stock market return. He had observed Karachi Stock Exchange 100 Index from 1974 to 2004 to figure out the relationship between stock price and economy. As the result, he proved that the inflation variable had showed no significant relationship to the stock price by implement granger causality test.

Song (1997) he used money supply oil price and inflation rate as explanatorily variables for Asian stock market. He used VAR model applied to observe the differences of the structure of fluctuation after 1997 financial crises. His finding oil prices and inflation are highly effect the stock market of Asian economy.

Hasan and Nasir (2009), test the relationship between inflation, industrial production, oil prices, short term interest rate, exchange rates, foreign portfolio investment, and money supply and equity price. They proved that ARDL long run coefficients reveal that inflation is not statistically significant in determining equity prices in long run.

Ahmed and Mustafa (2003) used data collected by basis of monthly data and annual data from 1972 to 2002 to study the effect of inflation towards stock prices index. They has found that control in the real output growth rate will impact negatively to real return. This proved by the finding from Fama (1981). However, the relationship between real returns and unexpected growth and unexpected inflation were significant but negatively trend to the stock return.

Adrangi, Chatrath, and Sanvicente (2002) (2002) used data obtained from the Brazilian Institute for Geography and Statistics (January 1986 to July 1997). The empirical tests are conducted within Fama’s proxy hypothesis framework, where the statement claim that there is a negative relationship between inflation and real activity; and the positive relationship between the real stock returns and real economic activity. They claim that there is negative relationship between inflation and the real stock returns but this does not obtained any results to support. In Brazil, the real stock and inflation rate showed negative relationship and this situation keep on going after the situation is purge on the negative relationship between inflation and real activity. So, inflation may can affected the real stock returns because the inflation pressure may threaten the corporate future profit, thus the nominal discount rate increase due to the inflationary pressures, current value of future profits been cut down, and the end is the stock return affected too. In the long-run relationship, price levels, stock price and the real activity had been proved is consistent result with the effect of hypothesis; and these findings were only occur in the long-run only.

From study carried out by Maysami, Lee, and Hamzah (2004) authors confirmed and concluded that the efficient market hypothesis in doubt was because of the co-integrating relationship between macroeconomic variables and stock prices. Principally, the behavior of stock market may definitely be predicted, contrary to the EMH conclusions and if affecting the stock market is not something they desire, policy-makers may need to re-