Abstract
We estimate tail parameters and construct risk statistics for unconditional distributions of daily logarithmic price changes of the NYMEX energy complex and apply the conditional extreme value method proposed by A. J. McNeil and R. Frey (2000) for estimating VAR and related risk statistics from the tails of conditional distributions for these commodities. The unconditional distribution of spot market price declines is found to be fat tailed relative to the normal for all commodities examined. Backtesting of candidate conditional risk measurement methods indicates that the conditional extreme value method is significantly more accurate for measuring risk exposure due to price declines for 7 of the 10 price series examined. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:309–337, 2005
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