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Value at Risk Based on the Volatility, Skewness and Kurtosis
Mar 1, 1999
This paper presents a new approach to calculating Value-at-Risk (VaR) in which skewness and kurtosis as well as the standard deviation or volatility are explicitly used. Based on the theory of estimating functions in statistics we construct an approximate confidence interval from the first two moment conditions. The final result shows explicitly how the confidence interval is affected by the standard deviation, skewness and kurtosis. We test our method using ten years of daily observations on twelve different foreign exchange spot rates and find the new approach captures the extreme tail much better than the standard VaR calculation method used in RiskMetrics™
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