Evaluation of VaR models' forecasting performance: the case of oil markets

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.