Empirical Analysis of Value-at-Risk Estimation Methods Using Extreme Value Theory

作     者：Zhao Yuanrui & Tian Hongwei School of Management, Finance Center, Tianjin University, 300072, P. R. China 

作者机构：School of Management Finance Center Tianjin University 300072 P. R. China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2001年第12卷第1期

页      面：13-21页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：the National Natural Science Foundation of China (No. 79970041) 

主　　题：Value-at-risk (VaR) Extreme value theory (EVT) Generalized extreme value distribution Twr-step subsample bootstrap Maximum likelihood estimation. 

摘      要：This paper investigates methods of value-at-risk (VaR) estimation using extreme value theory (EVT). It compares two different estimation methods, two-step subsample bootstrap based on moment estimation and maximum likelihood estimation (MLE), according to their theoretical bases and computation procedures. Then, the estimation results are analyzed together with those of normal method and empirical method. The empirical research of foreign exchange data shows that the EVT methods have good characters in estimating VaR under extreme conditions and two-step subsample bootstrap method is preferable to MLE.