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

Abstract

The financial crisis has fueled interest in alternatives to traditional asset classes that might be less affected 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 properties of the Dow Jones Islamic Stock Market Index (DJIM) and explore 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 volatility models are also in line with prevalent findings in the literature. With this proximity to standard asset classes, investments in the DJIM could hardly provide a cushion against extreme market fluctuations. Among the various models, the relatively new Markov-switching multifractal model performs best under the majority of time horizons and loss criteria. Long memory GARCH-type models (FIGARCH and FITVGARCH) always improve upon the short-memory GARCH specification and additionally allowing for regime changes can further improve their performance, and also enhance the accuracy of value-at-risk forecast.