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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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