摘要
将VaR和CVaR结合起来能全面描述金融时间序列与尾部相关的风险。考虑沪深股指收益序列胖尾特性,极值理论方法能够对沪深股市VaR和CVaR进行较好估计,运用基于Boot strap和极大似然估计方法解决极值理论数据不足的缺陷,从而给出对VaR和CVaR的点估计和区间估计。
Uniting VaR and CVaR can fully describe tailrelated risk. Since Shanghai and Shenzhen A Stock Market return distribution exhibit fat tails, the writers of this paper make use of extreme value theory to analyze VaR and CvaR on the two markets. Bootstrap method is used to reproduce subsamples to offset insufficient data. Bootstrap and likelihoodbased methods are also used to give point estimation and construct confidence intervals for the VaR and CVaR.
出处
《财贸研究》
北大核心
2005年第2期68-72,共5页
Finance and Trade Research