Nasr, Adnen BenLux, ThomasAjmi, Ahdi NoomenGupta, Rangan2016-09-062016-09Nasr, AB, Lux, T, Ajmi, AN & Gupta, R 2016, 'Forecasting the volatility of the Dow Jones Islamic Stock Market Index : long memory vs. regime switching', International Review of Economics and Finance, vol. 45, pp. 559-571.1059-0560 (print)1873-8036 (online)10.1016/j.iref.2016.07.014http://hdl.handle.net/2263/56631The nancial 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 properties of the DJIM index and explore its volatility dynamics using a number of up-to-date statistical models allowing for long memory and regime-switching dynamics. We nd 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 ndings in the literature. Overall, the relatively new Markov-switching multifractal model performs best under the majority of time horizons and loss criteria. Long memory GARCH-type models always improve upon the short-memory GARCH speci cation and additionally allowing for regime changes can further improve their performance.en© 2016 Elsevier Inc. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in International Review of Economics and Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Review of Economics and Finance, vol. 45, pp. 559-571, 2016. doi : 10.1016/j.iref.2016.07.014.Volatility dynamicsLong memoryMultifractalsIslamic financePostprint Article