Abstract
We investigate the performance of Value at Risk (VaR) models at measuring risk for WTI oil one-month futures returns. VaR models are used to calculate commodity market risk at extreme quantiles: 0.95, 0.99, 0.995 and 0.999 for both long and short trading positions. Widespread VaR models do not provide adequate risk coverage and their performance is especially weak for short position in oil. Conditional and unconditional extreme value theory VaR models are found to be the only ones correctly forecasting the true level of upside and downside risk. We also investigate the closeness of fit of theoretical distributions to the extreme tails of oil returns. Results show that generalised Pareto distribution provides the best fit to both tails of oil returns although tails differ significantly, with the right tail having a higher tail index, indicative of more extreme events.
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