Oil price changes and stock market returns: cointegration evidence from emerging market

Abstract

The aim of this paper is to examine whether changes in nominal oil prices (Brent and West Texas Intermediate (WTI)) affect the stock market returns in the context of an emerging market framework. The Autoregressive Distributed Lag bounds testing approach of cointegration is used to test for the long run relation between the two variables, where the daily stock market index return is calculated using the first difference in the natural logarithms of stock market index. Further, we test for the stability of the cointegration relationship by examining the sensitivity analysis where diagnostic tests for serial correlation (namely the Breusch–Godfrey serial correlations LM test) and cumulative sum of recursive residuals (CUSUM) are employed. Using daily data from January 3, 2000 to December 9, 2015, the findings suggest that there is long run integration between oil prices and stock returns series in which the daily oil price shocks have a negative impact on stock returns. The highly significant error correction coefficient indicates high rate of convergence to equilibrium. In addition, the Toda and Yamamoto (J Econom 66(2):225–250, 1995) Granger non‐causality test indicates significant bidirectional causality between stock market returns and Brent nominal oil price, meanwhile there is unidirectional causality running from WTI oil price to stock market returns. These findings are, up to some extent, meaningful for investors, portfolio managers and policy makers.