Forecasting the volatility of the Dow Jones Islamic Stock Market Index : long memory vs. regime switching

The financial crisis has fueled interest in alternatives to traditional asset classes that might be less a ected by large market gyrations and, thus, provide for a less volatile development of a portfolio. One attempt at selecting stocks that are less prone to extreme risks, is obeyance of Islamic Sharia rules. In this light, we investigate the statistical prop- erties of the Dow Jones Islamic Stock Market Index (DJIM) and ex- plore its volatility dynamics using a number of up-to-date statistical models allowing for long memory and regime-switching dynamics. We find that the DJIM shares all stylized facts of traditional asset classes, and estimation results and forecasting performance for various volatil- ity models are also in line with prevalent findings in the literature. Overall, the relatively new Markov-switching multifractal model per- forms best under the majority of time horizons and loss criteria. Long memory GARCH-type models always improve upon the short-memory GARCH specification and additionally allowing for regime changes can further improve their performance.