| 基于收益率修正分布的VaR估计 |
| |
| 引用本文： | 叶五一,缪柏其,吴振翔.基于收益率修正分布的VaR估计[J].数理统计与管理,2007,26(5):867-874. |
| |
| 作者姓名： | 叶五一 缪柏其 吴振翔 |
| |
| 作者单位： | 1. 中国科学技术大学统计与金融系,安徽合肥,230026
2. 中国科学院数学与系统科学研究院,北京,100080 |
| |
| 基金项目： | 国家自然科学基金;高等学校博士学科点专项科研项目;中国科学院和中国科技大学创新基金 |
| |
| 摘 要： | 本文针对正态分布在拟合厚尾分布上的不足提出了两种修正方法——参数修正方法和非参数修正方法,经过实证分析我们发现经过修正的分布能更好地拟合厚尾分布,相应的VaR值的预测效果也更好,其中非参数修正得到的VaR预测效果最佳。
|
| 关 键 词： | 非参数方法 均值回归 厚尾分布 在险价值VaR 事后检验 |
| 文章编号： | 1002-1566（2007）05-0867-08 |
| 修稿时间： | 2006-06-22 |
The Extimate for VaR Based on Modified Distribution of Return |
| |
| YE Wu-yi,MIAO Bai-qi,WU Zhen-xiang.The Extimate for VaR Based on Modified Distribution of Return[J].Application of Statistics and Management,2007,26(5):867-874. |
| |
| Authors: | YE Wu-yi MIAO Bai-qi WU Zhen-xiang |
| |
| Institution: | 1. Department of Statistics and Finance of USTC, Hefei Anhui, 230026 China; 2. Academy of Mathematics and Systems Science, CAS, Beijing, 100008 China |
| |
| Abstract: | In order to defect the flaw of the normal distribution when fitting the heavy tail distribution,in this paper,two modified methods were presented,which were Parametric and Nonparametric Modified Methods.By empirical analysis,the modified distribution can fit the heavy tail distribution better,and the forecasting effect of the VaR is better too,and the best forecasting result is that resulting from the nonparametric modified method. |
| |
| Keywords: | nonparametric methods mean regression heavy-tail distribution Value at risk(VaR) back-test methods |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
