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g-h分布和极值理论下的VaR估计
发表时间:2013-07-15 浏览量:1701 下载量:643
全部作者: | 丁芳,严定琪 |
作者单位: | 兰州大学数学统计学院 |
摘 要: | 为解决金融资产收益序列数据的尖峰厚尾性,在研究g-h分布一些特性的基础上,给出基于g-h分布的风险价值(risk at value,VaR)的估计,并比较了在极值理论下VaR值的估计。理论分析表明基于g-h分布的VaR值的估计更能准确描述资产收益率的变化。 |
关 键 词: | 概率论与数理统计;风险价值;g-h分布;极值理论 |
Title: | VaR estimate of g-h distribution and extreme value theory |
Author: | DING Fang, YAN Dingqi |
Organization: | School of Mathematics and Statistics, Lanzhou University |
Abstract: | In order to solve the problem of spike and fat-tail of financial assets sequence data, we gave the estimate value based on the g-h distribution of risk at value (VaR) on the basis of some features of the g-h distribution, and compared with the estimate of the value based on the extreme value theory. The analysis showed that the estimate value of VaR based on the g-h distribution could describe the changes in the rate of return on assets more accurately. |
Key words: | probability theory and mathematical statistics; risk at value; g-h distribution; extreme value theory |
发表期数: | 2013年7月第13期 |
引用格式: | 丁芳,严定琪. g-h分布和极值理论下的VaR估计[J]. 中国科技论文在线精品论文,2013,6(13):1192-1197. |
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