Forecasting volatility in Gulf Cooperation Council emerging markets: the predictive power of alternative models

Abstract

In this paper, a forecast of conditional volatility in Saudi, Kuwait and Abu-Dhabi markets is performed. To capture the skewness and excess kurtosis that characterise asset returns in Gulf Cooperation Council markets, the conditional volatility of asset returns was estimated using skewed t-distribution, symmetric student t-distribution and the Normal distribution specifications. Prediction performance results indicate that the normal and symmetric t-distribution models outperform the skewed t-distribution model.