Using Order Statistics to Estimate Confidence Intervals for Quantile-Based Risk Measures

被引：1
|
作者：
Dowd, Kevin
机构：
[1] Pensions Institute, Cass Business School, London
来源：
JOURNAL OF DERIVATIVES | 2010年 / 17卷 / 03期
关键词：
AVERSION;
D O I：
10.3905/jod.2010.17.3.009
中图分类号：
F8 [财政、金融];
学科分类号：
0202 ;
摘要：
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., mid 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
引用
收藏
页码：9 / 14
页数：6
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