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极值理论在风险度量中的应用--基于上证180指数
引用本文:田新时,郭海燕.极值理论在风险度量中的应用--基于上证180指数[J].运筹与管理,2004,13(1):106-111.
作者姓名:田新时  郭海燕
作者单位:华中科技大学,经济学院,金融系,湖北,武汉,430074
摘    要:精确度量风险是金融风险管理的关键问题。本引入广义帕雷托分布代替传统的正态分布等,精确描述金融收益的厚尾特征。并将基于广义帕雷托分布的VaR模型和其它模型方法,如GARCH(1,1)、GARCH(1,1)-t、历史模拟法、方差-协方差方法,进行比较分析。实证研究表明,基于广义帕雷托分布的VaR模型比传统的模型方法更适合厚尾分布高分位点的预测,并且其预测结果比较稳定。这使得基于广义帕雷托分布的VaR模型成为VaR度量方法中最稳健的方法之一。

关 键 词:极值理论  风险度量  金融风险管理  Value-at-Risk  GARCH模型
文章编号:1007-3221(2004)01-0106-06
修稿时间:2003年5月22日

The Application of Extreme Value Theory to Risk Measurement Based on SSE- 180 Index
TIAN Xin-shi,GUO Hai-yan.The Application of Extreme Value Theory to Risk Measurement Based on SSE- 180 Index[J].Operations Research and Management Science,2004,13(1):106-111.
Authors:TIAN Xin-shi  GUO Hai-yan
Abstract:The accurate estimation of Value-at-Risk(VaR) is essential for risk management.In this paper,we use the General Pareto Distribution(GPD)instead of Normal distribution to describe the heavy-tailed characteristic of financial time series.We compare this model with other well-known model such as GARCH(1,1),GARCH(1,1)-t,variance-covariance method and historical simulation.Our studies indicate that the model based on GPD fit better than traditional methods for heavy-tailed distribution on forecasting high quantiles, furthermore, the forecasting results of this model is more stable. This shows that this model is a robust tool to forecast quantiles,which is practical to implement and regulate for VaR measurements.
Keywords:finance risk management  value-at-risk  extreme value theory  GARCH model  
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