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 m...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.展开更多
根据g-h分布的统计特性,提出了基于投资组合极端损失的V aR计算方法——g-h V aR法.该方法结合了分析方法、历史模拟方法和极值理论方法的优点,能够较好地处理组合回报的不对称现象的厚尾现象.证券市场的实证研究表明,该方法优于常用的...根据g-h分布的统计特性,提出了基于投资组合极端损失的V aR计算方法——g-h V aR法.该方法结合了分析方法、历史模拟方法和极值理论方法的优点,能够较好地处理组合回报的不对称现象的厚尾现象.证券市场的实证研究表明,该方法优于常用的δ-正态方法.展开更多
基金the National Natural Science Foundation of China (No. 79970041).
文摘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.
