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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:1329  下载量:506
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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