Abstract
This investigation applies a composite Simpson’s rule, a numerical integral method, for estimating quantiles on the skewed generalized error distribution (SGED). Daily spot prices of Brent and WTI crude oil are used as data to examine the one-day-ahead VaR forecasting performance of the ARJI-N and ARJI-SGED models. Empirical results show that Brent (resp. WTI) crude oil exhibits slightly skewed to the left (resp right). Therefore the ARJI-SGED (resp. ARJI-N) model performs the better out-of-sample VaR performance for Brent (resp WTI) crude oil These findings demonstrate that the use of SGED distribution, which explicitly accommodates both skewness and kurtosis, is essential for out-of-sample VaR forecasting when the returns of financial assets exhibit skewed to the left.
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