TY - JOUR T1 - Using Order Statistics to Estimate Confidence Intervals for Quantile-Based Risk Measures JF - The Journal of Derivatives SP - 9 LP - 14 DO - 10.3905/jod.2010.17.3.009 VL - 17 IS - 3 AU - Kevin Dowd Y1 - 2010/02/28 UR - https://pm-research.com/content/17/3/9.abstract N2 - 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 ER -