This study assesses market risk in the international crude oil market from the perspective of VaR analysis. A GARCHSGT
approach is thus proposed capable of coping with fat-tails, leptokurtosis and skewness using SGT returns
innovations and catering for volatility clustering with the GARCH(1,1) model in modeling one-day-ahead VaR. This
technique is illustrated using daily returns of West Texas Intermediate crude oil spot prices from December 2003 to
December 2007. Empirical results indicate that the VaR forecast obtained by the GARCH-SGT model is superior to that
of the GARCH-T and GARCH-GED models through a series of rigorous model selection criteria. Overall, the
sophisticated SGT distributional assumption significantly benefits VaR forecasting for WTI crude oil returns at low and
high confidence levels, indicating a need for VaR models that consider fat-tails, leptokurtosis and skewness behaviors.
The GARCH-SGT model thus is a robust forecasting approach that can practically be implemented for VaR measurement.
Investment Management and Financial Innovations 6(1), pp.86-95