Markov Regime Switching Generalized Autoregressive Conditional Heteroskedastic Model and Volatility Modeling for Oil Returns

Samet G Nay
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Samet G Nay: Department of Finance, Business School, American University of the Middle East, Kuwait.
Authors registered in the RePEc Author Service: Samet Gunay

International Journal of Energy Economics and Policy, 2015, vol. 5, issue 4, 979-985

Abstract: In conjunction with the recent alternative models, a wide literature has been established for volatility modeling in finance theory. In this study, we examine return volatility of Brent oil returns through generalized autoregressive conditional heteroskedastic (GARCH), exponential GARCH, Glosten-Jagannathan-Runkle GARCH and Markov regime-switching GARCH (MRS-GARCH) models. As a preliminary test concerning the potential regimes, first, we use modified iterative cumulative sum of squares test in order to examine the existence of breaks in the variance of return series. All volatility models are formed under normal, generalized error distribution and Student s t distributions. According to the Akaike information criterion and Bayesian information criterion values, MRS-GARCH model outperforms all other alternative models. Another interesting result is the failure of the models that formed under normal distribution.

Keywords: Markov Regime Switching Generalized Autoregressive Conditional Heteroskedastic; Oil Volatility; Variance Breaks (search for similar items in EconPapers)
JEL-codes: C14 C22 C58 G14 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eco:journ2:2015-04-09

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