Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/96505
Authors: 
Nasr, Adnen Ben
Lux, Thomas
Ajm, Ahdi Noomen
Gupta, Rangan
Year of Publication: 
2014
Series/Report no.: 
Economics Working Paper, Christian-Albrechts-Universität Kiel, Department of Economics 2014-07
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. 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 specification and additionally allowing for regime changes can further improve their performance.
Subjects: 
islamic finance
volatility dynamics
long memory
multifractals
JEL: 
G15
G17
G23
Document Type: 
Working Paper

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