Impact Of Crude Oil Price Volatility On World Equity Markets Behavior
University of Delhi
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Islamic Azad University (IAU)
Journal of Applied Research in Finance, 2011
In the age of globalization, it has become very important to find out the economic and non variables which are significantly responsible for volatility in stock markets. Investors have become largely sensitive to these factors which results in change their investment strategy at the time of emergence on national and international level. The present study is an attempt to measure how equity markets of developed and developing countries respond to volatility in international crude oil price. To investigate the problem, the study uses a set of ten stock markets from developed countries and seven stock markets from developing countries. To analysis how investors react to crude oil price volatility which results in volatility in stock market, two stages GARCH (1,1) model is used. In the first stage, GARCH (1,1) is used to estimate the conditional volatility of crude oil price expressed in dollar, thereafter in the second stage, the estimated conditional volatility of crude oil price is used as independent regressor to estimate the conditional volatility of world equity markets in question by running GARCH (1,1) model. The data set used in the study involves the monthly prices of stock exchange listed indices for the period ranging from January 1995 through December 2007. In brief, the research methodology applied in the study includes application of Jarque-Bera test to determine the normality of data, Ljung-Box to examine the cross correlation in stock returns, GARCH (1,1) estimation of asymmetric volatility, and finally correlation to examine the volatility integration between world equity markets returns and crude oil price in the international market. The results reveal the following – Oil prices are normally distributed during the study time period; The significance of Jarque Bera statistics indicates that out of developed countries, Japan stock market and out of developing countries, India and China stock markets returns are normally distributed; On an average, stock markets of developing countries have offered higher average return to the investors; The first stage GARCH (1,1) results of oil price exhibit that oil price volatility is significantly influenced by unexpected events in international markets and volatility in preceding time periods ; The second stage GARCH (1,1) results exhibits that crude oil price volatility significantly determines the stocks markets return volatility of both developed and developing countries. The direct observations can be made here that investors are largely sensitive to fluctuations in crude oil prices in the international market; Correlation matrix of stock markets return volatility and crude oil price volatility in case of both developed and developing countries exhibit a higher degree of correlation. These results bring out the corresponding relation between crude oil price volatility and stock markets return volatility.
Impact Of Crude Oil Price Volatility On World Equity Markets Behavior – Introduction
A forecast of oil price volatility works important input into macroeconomic econometric models for the assessment of risk and return of financial markets, and modeling of volatility. Recent empirical works suggest that oil price shocks tend to have an adverse impact on the macro economy as a whole and stock market as particular. This paper provides empirical support for this proposition by showing the correlation of a set of world equity markets return volatility and crude oil price volatility, measured by conditional variance of oil prices, which helps to forecast stock market movements. A part of the asymmetric movements in stock returns reported in previous studies can be explained by taking crude oil price volatility as independent regressor in forecasting the stock market volatility.
In fact, with starting the deregulation phase of financial sector, world equity markets are reporting integration to large or less extent. Researchers and policy makers are largely interested in exploring the economic and non-economic factors responsible for stimulating the investors to respond in the same line over the development of these factors. Stock prices are generally believed to be determined by some fundament macro-economic variables such as interest rate, exchange rate, and inflation rates. For global and domestic investors, a highly integrated world equity market indicates that returns of securities are similarly priced internationally in response to global economic and non-economic factors. The emergence of this phenomenon reduces to earn risk premium in diverting funds from one market to another and potential opportunities for global diversification. For corporate, a highly integrated world equity market signifies that there are little opportunities to raise capital at lower cost across the border markets, however, as a matter of fact, the dominate factors are out of explanation yet which are promoting world equity market integration. The present study attempts to investigate the volatility in world equity markets caused by fluctuations in crude oil prices in international market. Oil price volatility creates uncertainty among the investors and their investment decisions therefore tend to become sensitive to volatility in crude oil prices. In the post war period especially after 1986, oil price hikes have reported a significant and deterministic effect on stock markets.
The study also attempts to measure the integration in volatility of stock markets with respect to crude oil prices. A substantial work is found in case of interdependency of developed stock markets, however very less efforts are made to explore the dynamics between crude oil price volatility and stock market returns volatility. Studies (Hamao et al.. 1990; Kumar and Mukhopadya 2002) employed two stages GARCH model to study the dynamic relationship across the stock markets wherein day time and overnight returns are used. They firstly extracted the unexpected shocks from the day time returns of one market and used it as a proxy for volatility surprise while modeling the other markets overnight returns in the second stage of modeling. Further, number of studies (Cheung and Mak 1992; Karolyi and Stulz, 1996; Masih and Masih 2001) employed co-integration and Gragnger causality test and held that US stock market contributes dominate role in world stock market integration. Studies (Mcclure et al.., 1999; Huang Yang and Hu, 2000; Jong and Roon, 2001; Mukherjee and Mishra, 2007) examined group stock markets and held a strong interdependence across the stock markets. Further, number of empirical studies examines the integration of stock markets and possible dynamics like interest rate, foreign investment, trade relations, inflation which integrates the markets (Black and Fraser, 1995; Bracker et al.., 1999; Wu, 2001; Pretorius, 2002; Liu et al.., 2006). The recent liberations of financial system and accelerating trade relations, have also integrated the world equity markets as whole to more or lesser degree. . Cheung et al.. (1998) apply co-integration technique in finding out long run co-movements between five national stock market indices and measures of aggregate real activity including the real oil price, real consumption, real money, and real output. Real returns on these indexes are typically related to transitory deviations from the long run relationship and to changes in the macroeconomic variables. Further, the constraints implied by the co-integration results yield some incremental information on stock return variation that is not already contained in dividend yields, interest rate spreads, and future GNP growth rates.
Ewing et al.. (1999) examined how the North America Foreign Trade Agreement (NAFTA) affected the level of market integration in North America, it however found no evidence of integration in member markets even after the NAFTA agreements was embedded. Sasaki et al.. (1999) examined the dynamic relationship in accordance with the monetary policies and found significant evidence that monetary variables affect the international interdependencies across stock markets. In conclusions, majority of studies suggested that market integration has increased significantly over the years, however, number of studies yet questions over this phenomenon, and failed to report any dynamic relationship (Cheung and Lee, 1993; King et al.., 1994; McClure et al.., 1999, Ewing et al.., 1999). Gjerde (1999) investigates the utility of the results on relations among stock returns and macroeconomic factors from major markets on a small and open economy by applying multivariate vector autoregressive (VAR) approach on Norwegian stock market data. Consistent with US and Japanese findings, real interest rate changes affect both stock returns and inflation, and the stock market responds accurately to oil price changes. On the other hand, the stock market shows a delayed response to changes in domestic real activity.
Sadorsky (1999) employs vector auto regression to examine the dynamics between crude oil prices, interest rate and stocks returns. The study reports that oil prices and oil price volatility both play important roles in affecting real stock returns. After 1986, oil price movements explain a larger fraction of the forecast error variance in real stock returns compare to interest rates. There is also evidence that oil price volatility shocks have asymmetric effects on the economy. Study of Darrat and Zhong (2001) however produced the opposite results wherein markets of US, Canada, Mexico were examined. By applying the co-integration tests their results suggested NAFTA enhanced the linkages across member stock markets. Some empirical studies hold monetary variables as dynamics of linkages between stock markets. Papapetrou (2001) attempts to shed light into the dynamic relationship among oil prices, real stock prices, interest rates, real economic activity and employment for Greece by using the multivariate auto regression model. The empirical evidence suggests that oil price changes affect real economic activity and employment. Oil prices are important in explaining stock price movements; however stock returns do not lead to changes in real activity and employment. Sadorsky (2006) study further uses univariate and multivariate models to estimate forecasts of daily volatility in petroleum futures price returns wherein the out-of-sample forecasts are evaluated using forecast accuracy tests and market timing tests. The TGARCH model fits well for heating oil and natural gas volatility and the GARCH model fits well for crude oil and unleaded gasoline volatility. Simple moving average models seem to fit well in some cases provided the correct order is chosen. The study reports that used models out perform a random walk and there is evidence of market timing. Non-parametric models outperform the parametric models in terms of number of exceedences in backtests.
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