This paper investigates the dynamics of the co-movement of GCC stock market returns with global oil market uncertainty, using an ARMA-DCC-EGARCH and time varying Student-t copula models. Empirical results demonstrate that oil uncertainty has significant and time varying impacts on the GCC stock returns. The GCC stock returns are found to be negatively affected by oil market uncertainty for almost the entire period under examination. More interestingly, we find that the impact of oil price uncertainty differs across GCC member states and allow for grouping. The results also show that the stock markets of Oman and Bahrain are relatively less sensitive to the oil uncertainty factor, thus offering investors and portfolio managers different investment options and portfolio diversification opportunities across GCC members.

Stock return predictability has always been one of the central themes of finance literature, given its crucial implications for investment decisions, risk management, and financial and monetary policymaking. This paper evaluates the in-sample and out-of-sample stock return predictive power of the global and Saudi geopolitical risk indices and crude oil returns in the context of six Gulf Cooperation Council (GCC) countries. Monthly data from February 2007 to December 2019 and the feasible generalized least square (FGLS) estimator for predictive modelling by Westerlund and Narayan (2012, 2015) are used. Global and Saudi GPR indices show weak evidence of in-sample predictability of excess stock returns. However, the out-of-sample forecasts show that only the global geopolitical risk index provides superior prediction in the context of Kuwaiti and Omani stock markets, compared to the historical average benchmark model. Crude oil prices are shown to be a better predictor in most cases, in both in-sample and out-of-sample forecast models The results imply that crude oil returns can be used for active prediction of GCC stock market returns, once econometric issues are accounted for. The findings remain mostly unaffected when excess risk adjusted returns are used.

This study examines the long run impacts of equity market volatility on index returns of nine major international stock exchanges in the Western and Asian regions. This study employs the text-based Economic Market Volatility (EMV) index to measure the degree of uncertainty in the U.S. stock market. Using monthly data from December 2001 to August 2018, the estimation results derived using the standard and nonlinear ARDL models deliver several key messages. First, rising U. S. stock market volatility exhibits significant and negative impacts on stock market returns, except for the stock markets of China, Hong Kong, and India whose impacts are negative but insignificant. Second, the use of the nonlinear ARDL model does not show any signs of asymmetry in the relationship between stock market returns and changes in the EMV index, suggesting that the change in the EMV index has symmetric effects on the changes in major stock indices.