PT - JOURNAL ARTICLE AU - Kevin Dowd TI - Using Order Statistics to Estimate Confidence Intervals for Quantile-Based Risk Measures AID - 10.3905/jod.2010.17.3.009 DP - 2010 Feb 28 TA - The Journal of Derivatives PG - 9--14 VI - 17 IP - 3 4099 - https://pm-research.com/content/17/3/9.short 4100 - https://pm-research.com/content/17/3/9.full AB - This article shows how to apply the theory of order statistics to estimate confidence intervals for quantile-based risk measures, a class that includes the VaR, expected shortfall, and coherent, convex, and spectral risk measures. The proposed method can be applied to any parametric or nonparametric loss distribution, has a number of advantages relative to alternative methods of estimating confidence intervals for financial risk measures, and is straightforward to implement.TOPICS: VAR and use of alternative risk measures of trading risk, derivatives