Evaluation of VaR models' forecasting performance: the case of oil markets
by Med Imen Gallali; Raggad Zahraa
International Journal of Financial Services Management (IJFSM), Vol. 5, No. 3, 2012

Abstract: This paper highlights the importance of Value-at-Risk (VaR) methodology in managing oil market risks of three international crude oil rates (Brent, OPEP and WTI). Comparing between the conventional VaR models proposed by the literature (non-parametric models, hybrid models and conditional and unconditional parametric models), we point to the supremacy of conditional GARCH-type models (GARCH-T) or hybrid models (Filtered Historical Simulation). In contrast, the unconditional models or those based on the normality hypothesis are the least performing. In general, there is a tendency to prefer the conditional models as they allow integrating the dynamic nature of volatility and distributions flat tails.

Online publication date: Sat, 29-Nov-2014

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