Nonparametric estimation of value-at-risk

被引：9
|
作者：
Jeong, Seok-Oh [1 ]
Kang, Kee-Hoon [1 ]
机构：
[1] Hankuk Univ Foreign Studies, Dept Stat, Yongin, South Korea
来源：
JOURNAL OF APPLIED STATISTICS | 2009年 / 36卷 / 11期
关键词：
value-at-risk; volatility; local homogeneity; quantile estimation; risk management; KOSPI; MODELS;
D O I：
10.1080/02664760802607517
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
This paper develops a fully nonparametric method for estimating value-at-risk based on the adaptive volatility estimation and the nonparametric quantile estimation. The proposed method is simple, fast and easy to implement. We evaluated its numerical performance on the basis of Monte Carlo study for numerous models. We also provided an empirical application to KOrean Stock Price Index data, which turned out to be successful by backtesting.
引用
收藏
页码：1225 / 1238
页数：14
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