RT Journal Article SR Electronic T1 Using Order Statistics to Estimate Confidence Intervals for Quantile-Based Risk Measures JF The Journal of Derivatives FD Institutional Investor Journals SP 9 OP 14 DO 10.3905/jod.2010.17.3.009 VO 17 IS 3 A1 Kevin Dowd YR 2010 UL https://pm-research.com/content/17/3/9.abstract 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