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-evaluate their economic policy. The fact that specific sectors represented in the SGX were individually affected by to different extent by various macroeconomic variables points to the possibility of superior returns based on selecting stocks from specific sectors of the economy as information had becomes available on specific macroeconomic variables. Policy-makers need to be careful too when they want to use changes in macroeconomic variables such as the money supply, interest rates, or the exchange rate as the tool to influence the economy. Policy maker may unintentionally lower the stock market, and curtail capital formation which itself would lead to further slowdown of the economy in order to cross over the macroeconomic ills such as inflation or unemployment.
Gunsel and Cukur (2007) employ the method of Durbin-Waltson Statistics and OLS technique to test the relationship between the macroeconomic variables such as interest rate, risk premium, exchange rate, money supply, inflation, industrial production and dividend yield and the stock return in London. They obtained data from Datastream from January 1980 to December 1993. As the result, they found that there was no significant relationship between unexpected inflation and the stock return. This is because before the announcement, the market predicts it and incorporates into the stock prices. The effective exchange rate showed the relationship to the stock price movement and pointed as important factor by the researchers in two industries, building materials and merchants & engineering. Both industries suffered because of the exchange rate movement.
Anokye and George (2009) obtained quarterly data from DSI, COI, EX, TB and FDI from January 1991 to April 2006 to test the relationship between the macroeconomic variables and the stock market index return. They used Johansen’s multivariate co integration test & VECM to run this test. As the result, they proved that there is positive relationship between the inflation to DSI. This result was supported by the finding from Firth (1979), Anari and Kolari (2001), Luintel and Paudyal (2006), and Gultekin (1983) where they concluded that the inflation was used by the market as hedging method for the stock. Besides, they also found that interest rate and exchange rate had small impact to the share price but not as the inflation rate and net FDI inflow. Thus, Anokye and George (2009) suggested that investors should focus on the inflation rate and exchange rate, followed by the net FDI inflow but not in interest rate.
2.2.2. Relationship between exchange rates and stock returns
Mohammad, Hussain, and Ali (2009) used descriptive statistics & auto regressive integrated moving average (ARIMA) model testing to study Stock Prices from KSE collected from year 1986 to 2008. The major purpose is to examine the relationship between macroeconomic variables and Karachi stock market. As the result, they found that they exchange rate and exchange reserve had highly influenced the stock price movement. This phenomena clearly showed in the period after liberalization in 1991 of stock market in Pakistan where largely increasing stock prices.
Manish and Aggarwal (2011) had find out the relationship between macroeconomic variable such as Exchange rate, USA GDP, S&P, USA interest rate, Gold Price, WPI, Fiscal Deficit, IIP with the stock price movement in the Indian Capital Market. They had observed from year 1994 to 2010 of the stock market in India and found that these variables were significant relationship to the stock prices.
Islam (2003) simulated the similar research to figure out the short-run dynamic and long-run equilibrium relationships between macroeconomic variables which include interest rate, inflation rate, exchange rate, and the industrial productivity and the Kuala Lumpur Stock Exchange (KLSE) Composite Index. Islam concluded that significant result showed between these macroeconomic variable and KLSE stock return in the short-run dynamic and long-run equilibrium relationship.
Ibrahim (1999) had concluded that Malaysian stock market’s information was inefficient. He had investigated the relationship between macroeconomic variable include industrial production index, money supply M1 and M2, consumer price index, foreign reserves, credit aggregates and exchange rate; and KLSE Composite Index. Ibrahim (1999) result was supported by Chong and Goh (2003) where they figure out that stock prices, economic activities, real interest rates and real money balances in Malaysia were linked in the long run both in the pre- and post capital control sub periods.
Gunasekarage, Pisedtasalasai and Power (2004) observed month data for 17 years period from January 1985 to December 2001 with use co-integration to test the short-run and VECM to test long-run relationship between the stock market index which represent by the Colombo All Share price index; with the economic variable such as the money supply, the treasury bill rate (as a measure of interest rates), the consumer price index (as a measure of inflation), and the exchange rate. Through their research, the money supply, the exchange rate had a significant influence on the stock market and their findings were supported by the VECM analysis.
Solnik (1987) had found and proved that non-significant relationship between the exchange rate and the stock price. At the mean while, Soenen and Hennigar (1998) had claim that US dollar effective exchange rate had not significant relationship to the US stock market index in the period 1980 to 1986. But, later in Jorion (1990) had found and showed that the relationship between stock return of US multinational companies and the effective US dollar exchange rate for the period 1971 to 1987. Continue Aggarwal (1981) found the similar positive relationship between stock return in US and the exchange rate. Mukherjee and Naka (1995) had showed the same significant relationship between stock return in Japan and Indonesia and exchange rate.
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 exchange rates and money supply have significant long run effect on equity prices. As the finding, they claim that in order to let investors can estimate the future direction of equity prices and can allocate their resource more efficiently, investors should taking effective investment decisions as by estimating the expected trends in exchange rates, money supply and interest rate. Capital markets have been responding to arrival of new information in efficient market hypothesis. So, macroeconomic policies should be designed keeping in view the response of the capital market and architects of monetary policy should be careful in revision of interest rates as capital market responds negatively to such decisions. At the same time, impact of money supply on capital markets should consider by the State Bank of Pakistan as there is significant relationship with the equity returns.
In another study by Pilinkus and Boguslaukas (2009), the results were clearly indicated that in Lithuania, stock market prices were significant determined by the macroeconomic variables. The stock market prices have related positive relationship to the gross domestic product and money supply; but, unemployment rate, exchange rate, and short-term interest rates have showed the negative influence on the stock market prices. They claimed that it is the best example of an unstable relationship between a macroeconomic variable and stock market prices in Lithuania when harmonized consumer price index is been consider.
Ahmad, Rehman, and Raoof (2010); used data collected from 1998 to 2009 on yearly basis from the State Bank of Pakistan and Karachi Stock Exchange to study relationship between stock market return with interest rate and exchange rate. From their study, the macro economic variables resulted significant impact on stock market. Similar is the case with the change in exchange rate but in opposite direction. The results give a clear indication that the change in interest rate and exchange rate has a significant impact on stock returns. The change in exchange rate has a positive impact.
Abdelaziz and Chortareas (2008) held a study in four countries in 2008 and found out that the oil price is an important variable, which acts as a conduit because the real exchange rates and domestic stock prices were connected. As the oil exporting countries, they should look at the effect of changes in the oil price level on their country economy and stock markets. Besides, the real exchange rates and stock prices might influence by the government policy makers. The portfolio managers who interested in the global asset allocation or investors who trying to hedge against foreign exchange risk; can look into the relationship between real exchange rates and stock prices. Last but not least, the authors claim that there is no relationships between the real exchange rates, stock prices but US stock market provide the foreign investors an opportunity to obtain advantages from that in diversifying their portfolio between the major stock market and the emerging markets.
Empirical study by Sheng and Shuh (2004) with 1045 observations had get supports the asymmetric volatility spillover affect and shows that movements of stock prices will affect future exchange rate movements. But the future changes of stock price will get less direct impact on the changes in exchange rate. This finding is important to the international portfolio manager for them to devising hedging and diversification strategies for their portfolio.
Jeffrey (2008) used 4,167 observations on daily closing Singapore Index and daily closing foreign exchange rate to study the relationship of exchange rate and Singapore Index. The result showed when in the Asian Financial Crisis, the prices in equity markets lead by the exchange rates. But this situation is excluded in the 1997 Financial Crisis to incident 911, and from incident 911 to 2006. The relationship between stock prices and exchange rate differs depend on the time series tested in Singapore.
By using daily closing price of S&P CNX Nifty Index and INR/USD from 4th January 1999 to 31st August 2009; Kumar (2009) proven that the bidirectional linear and nonlinear causality from index returns to exchange rate returns and from exchange return to index returns. But the result was disagreeing by the finding from Muhammad and Rasheed (2002) and Rahman and Uddin (2009). Kumar (2009) result was useful for regulators, market participants and academicians. He suggested that in order to predict the stock prices and exchange rate future movement, the market participants should consider the relationship between the exchange rate and stock index. Besides, this also can assist the regulators to realize the structure of the market in a better way and in the design of the policy. Kumar (2009) also suggested that India should cautious in conducting the exchange rate policies or capital market policies as it may direct influence the country’s financial market development.
Research paper presented by Rahman and Uddin (2009) revealed that stock prices does not Granger cause exchange rates and exchange rates does not Granger cause stock prices, so there is no way cause relationship between stock prices and exchange rates. Authors claimed that the variables are not expected on the basic of the past values of other variables. Their finding showed that there is no speculation opportunity in the stock market or foreign exchange market. The market participants cannot utilize the information of the market to improve the forecast of the other market since there is no relationship between the stock prices and exchange rates.
With 1,080 observation monthly data of stock market price index, exchange rate and oil price obtained from March 1993 to June 2006, Gay (2008) with used method of Boc-Jenkins ARIMA model to test the relationship between macroeconomic variable of exchange rate and crude oil price; and the stock market index return in four emerging economies which form by Brazil, Russia, India and China. He found that there was no significant relationship between these macroeconomic variables to the BRIC stock market index price. He explained that this situation might because of the influence of other than domestic and international macroeconomic factor on the stock market returns.
Chowdhury et al., (2006) with employ GARCH (Generalized Autoregressive Conditional Heteroskedasticity) to figure out the relationship between Inflation, Industrial production index, foreign exchange rate and consumer price index with stock market return. Monthly composite DSE index, Industrial production index, foreign exchange rate and consumer price index obtained from January 1990 until December 2004 in this research. As the result, the relationship between macroeconomic variables and the stock market return were not significant. The relationship between variables of exchange rate with and stock market can be defined by implement the policy of the fixed exchange rate. Besides, they conclude that volatility shocks to every macroeconomic variable were very consistent and take a long period to digest.
2.2.3. Relationship between interest rates and stock returns
Mohammad et al., (2009) used Descriptive statistics & auto regressive integrated moving average (ARIMA) model testing to study Stock Prices from KSE collected from year 1986 to 2008. The major purpose is to examine the relationship between macroeconomic variables and Karachi stock market. They found that interest rate and money supply did show the significant relationship to the stock price movement but in the negative trend.
Mala and Reddy (2007) research the level of volatility (risk) presence in Fiji’s stock market, which consider still in the emerging by using the autoregressive conditional heteroskedasticity (ARCH) models & GARCH models. Data collected from year 2001 to 2005 which selected 16 listed companies on the stock market only 7 firms were volatile; these firms which have appeared to be volatile are the ones which were sensitive to government regulations, where the liquidity had been low over the years and where the IPOs had been quite under price. They found and indicated the role of the interest rate on the volatility of stock return; where the interest rates regressed with the stock returns, the ARCH term and interest variable is significant.
Bilson (1999) claim that interest rates in emerging economic have grown over the past decade and this situation include in the case in Fiji Islands. In the previous research found that increase in the interest rates will impact on the stock return volatility. This suggest that wide range of factors example goods prices, money supply, real activity, exchange rates, political risks, oil prices, trade sector, and regional stock market indices will impact in the stock return volatility. Thus, they finalized that volatility in the stock return of a firm stems from the fact that stock returns may no longer be seen as the true intrinsic value of a firm and thus the investors might start losing confidence in the stock market.
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. Continue, through the causality test, he suggested that there is a unidirectional causal relationship between stock market volatility and interest rate volatility with the direction from stock prices to the interest rate. He claimed that the stock price movement should be a sign of future corporate performance. This is because the corporate profits generally may reflect the level of country’s economic activities. Thus, if the stock prices accurately represent the underlying fundamentals, then the leading indicators of future economic activity should as the stock prices.
Habibullah and Baharumshah (2000) implement Yamomoto (1995) methodology to figure out the relationship Malaysian stock market and macroeconomic variables which include money supply, gross national product, price level (Consumer Price Index), interest rate (3-month Treasury bill rate) and exchange rate (real effective exchange rate) and the study used quarterly data for the sample period January 1981 to April 1994. They found that stock price lead nominal income, the price level and the exchange rate, but money supply and interest rate lead stock prices in Malaysia.
Islam and Watanapalachaikul (2003) had examined the relationship between stock prices in Thailand and macroeconomic factors. This research had collected the data from year 1992 to 2001. They concluded that there is a significant relationship in the long-run between the macroeconomic factors such as interest rate, bonds price, foreign exchange rate, price-earnings ratio, market capitalization, and consumer price index with the stock prices in Thailand.
Through the co-integration analysis by error correction mechanisms (ECM), Omran (2003) result showed that significant relationship in the short-run and the long-run between the interest rate and the performance of the Egyptian stock market. He concluded that the real interest rate had an impact upon stock market performance.
Gunasekarage, Pisedtasalasai and Power (2004) observed month data for 17 years period from January 1985 to December 2001 with use co-integration to test the short-run and VECM to test long-run relationship between the stock market index which represent by the Colombo All Share price index; with the economic variable such as the money supply, the treasury bill rate (as a measure of interest rates), the consumer price index (as a measure of inflation), and the exchange rate. Through their research, the money supply, the Treasury bill rate had a significant influence on the stock market and their findings were supported by the VECM analysis.
Beenstock and Chan (1988) had concluded that unanticipated increase in the interest rate will slow down the stock return. They employed 4 risk factors such as interest rates, money supply (M3), fuel and material cost, and the retail price index against the return of stock market. Hamao (1988) shows that inflation has significantly influenced Japanese stock returns. An investigation of the relationships between stock prices and real activity, inflation, and money conducted by Fama in 1981 shows a strong positive correlation between common stock returns and real variables. Later, Kaneko and Lee (1995) and Lee (1992) find similar results. However, by examining the relationship between inflation and stock prices in 16 industrialized countries, Rapach (2002) argues that increase in inflation does not result in persistent depreciation of share real value.
Opportunity costs of holding cash rises with increase in interest rate, and the trade-off to holding other interest bearing securities would lead to a decrease in share price. Gan, Lee, Young, and Zhang (2006) and French, Schwert and Stambaugh (1987) had found the negative relationship between stock return and the interest rate in both short and long term. However, Bulmash and Trivoli (1991) claimed that there is significant relationship between US Stock markets with US stock price, money supply, federal debt, tax-exempt government debt, long-term unemployment, the broad money supply.
With employed CPI, IIP, money supply and foreign exchange rate as dependents variable, Nishat & 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 claim that the variable of interest rate showed not cause scientifically to stock price under his findings.
Cifter and Ozun (2007) had examined the relationship between the macroeconomic factors including interest rates with the stock returns. They expected there is negative impact on the interest rate on stock returns, result showed as assumption. By using daily closing values of the ISE 100 Index and compounded interest rates, it is proven that and starting with 9 days time-scale effect interest rate is granger cause of ISE 100 Index and the effects of interest rates on stock return increases with higher time-scales. The finding is the bond market has significant relationship in the long-term where effect the stock market movement in Turkey and suggested the traders should take in consider long-term money market changes as well as short term changes. Moreover, they also suggested that expected investors should follow the volatility in the interest rates to take decisions in their capital market investments for more than 9 days trading position.
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 interest rates have significant long run effect on equity prices.
Alam and Uddin (2009), using samples collected from fifteen countries from January 1988 to March, discover that the theoretical argument of negative relationship between stock price and prevailing interest rate is accepted. The countries tested include Australia, Bangladesh, Canada, Chile, Colombia, Germany, Italy, Jamaica, Japan, Malaysia, Mexico, Philippine, S. Africa, Spain, and Venezuela. As a result, they figure out that Malaysia it is found that share price has no related to the interest rate, but the changes of interest rates has negative relationship with the changes on the share price. In Japan, authors showed that positive relationship between the share price and the interest rate, but negative relationship in change of interest rate and change of share price as in Malaysia. Four countries as Bangladesh, Colombia, Italy, and S. Africa shows negative relationship for interest rates with share price and the changes of interest rates with changes of share price. Besides, eight countries as Australia, Canada, Chile, Germany, Jamaica, Mexico, Spain, and Venezuela had showed significant negative relationship between interest rates and share price, but there were no relationship between the change of interest rate and share price. Through their research’ result, Philippine is the one countries did not show significant negative relationship either interest rates with share price or the changes of interest rate with changes of share price or both. As conclude, they wind up that for these countries that able to control the interest rate, they can obtain benefit for their stock exchange through demand pull way of more investor in share market, and supply push way of more extensional investment of companies.
Christopher, Rufus, and Ezekiel (2009) found that stock price have direct affected by the forces of demand and supply while the demand and supply factors were influenced by the indeterminate number of firm, industry and country factors. This
Cite This Work
To export a reference to this article please select a referencing stye below:
Related ServicesView all
Related ContentAll Tags
Content relating to: "Economics"
Economics is the science of how economies work with regards to the production and consumption of goods and services and the analysis of a society’s commercial activities.
Non-performing Loans and Bank Performance During Economic Crisis
This study is focused on the effect of nonperforming loans of Public Bank toward macroeconomic variable. Viewing quarterly in 2005 to 2009 as a reference of investigation, it can be used for bankers as a benchmark for their future planning....
Food Processing in Agricultural Regions
Agricultural regions in any country, including the United Kingdom, have historically been seen as poorer neighbours to the more industrialised areas of any particular country (Pierpont 1997). This pos...
DMCA / Removal Request
If you are the original writer of this literature review and no longer wish to have your work published on the UKDiss.com website then please: