A wavelet analysis of mean and volatility spillovers between oil and BRICS stock markets

This paper investigates the spillover effects of volatility and shocks between oil prices and the BRICS stock markets using multivariate approach and wavelet analysis at different time horizons. Hence, we combine a multivariate ARMA-GARCH model and wavelet multiresolution analysis to study this phenomenon. A bivariate ARMA(1,1)-GARCH(1,1)-cDCC-Student-t model was joined with MODWT filter to capture a broad range of possible spillover effects in mean and variances of level prices at various time horizons. Generally, empirical results provide strong evidence of time-varying volatility in all markets under study. However, our proposed approach shows that oil price and stock market prices are directly affected by their own news and volatilities and indirectly affected by the volatilities of other prices and wavelet scale. The results show also, that mean and volatility spillover effects was decomposed into many sub-spillovers on different time scales according to heterogeneous investors and market participants. The practical implications of this study are critical, innovative and useful for the local and international investors and also for the portfolio managers. They can utilize this study to formulate the optimal oil-BRICKS stock portfolios as well as lead to more accurate predictions of volatility spillovers patterns also in developing their hedging strategies. (C) 2017 Published by Elsevier B.V.