| 极值理论在高频数据中的VaR和CVaR风险价值研究 |
| |
| 引用本文： | 赵树然,任培民.极值理论在高频数据中的VaR和CVaR风险价值研究[J].运筹与管理,2007,16(6):128-132. |
| |
| 作者姓名： | 赵树然 任培民 |
| |
| 作者单位： | 1. 北京理工大学理学院数学系,北京,100081
2. 青岛大学经济学院,山东青岛,266071 |
| |
| 摘 要： | 高频数据具有与低频数据明显不同的特征。本文引入广义帕雷托分布代替传统的正态分布等,精确描述金融高频数据收益的厚尾特征;并且计算高频数据下的VaR和CVaR,然后利用深成A指数据进行返回检验。两种返回检验方法的结果表明,极值理论方法可以比较精确地度量VaR和CVaR。
|
| 关 键 词： | 金融学 风险价值(VaR) 条件风险价值(CVaR) 极值理论 高频数据 |
| 文章编号： | 1007-3221（2007）06-0128-05 |
| 收稿时间： | 2007-05-19 |
| 修稿时间： | 2007年5月19日 |
Studies on VaR and CVaR for High Frequency Data Based on Extreme Value Theory |
| |
| ZHAO Shu-ran,REN Pei-min.Studies on VaR and CVaR for High Frequency Data Based on Extreme Value Theory[J].Operations Research and Management Science,2007,16(6):128-132. |
| |
| Authors: | ZHAO Shu-ran REN Pei-min |
| |
| Abstract: | High frequency data has entire different characteristics with lower frequency data.In the paper,replacing some conventional distributions such as normal distributions,a generalized pareto distribution is introduced to finely describe the characteristics of the tail of return for high frequency data,and further to estimate the VaR and CVaR.The two statistical tests for the data of Shenzhen index A are conducted and the results indicate that VaR and CVaR can be precisely estimated by the method of extreme value theory. |
| |
| Keywords: | finance value at risk(VaR) conditional value at risk(CVaR) extreme value theories high frequency data |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
