厚尾分布情形下的信用资产组合风险度量

被引：8

作者：

陈荣达 ^{[1
,2
,3
]}

王泽 ^{[1
]}

李泽西 ^{[1
]}

王聪聪 ^{[1
]}

余乐安 ^{[4
]}

何牧原 ^{[5
]}

机构：

[1] 浙江财经大学金融学院

[2] 浙江财经大学财富管理与量化投资协同创新中心

[3] 浙江省政府管制与公共政策研究中心

[4] 北京化工大学经济管理学院

[5] 清华大学经济管理学院

来源：

管理科学学报 | 2017年 / 20卷 / 03期

关键词：

资产组合; 厚尾分布; 结构模型; 重要抽样技术;

D O I：

暂无

中图分类号：

F224 [经济数学方法]; F830 [金融、银行理论];

学科分类号：

0701 ; 070104 ; 1201 ; 020204 ;

摘要：

本文研究风险因子多元厚尾分布情形下的信用资产组合风险度量问题.用多元t-Copula分布来描述标的资产收益率分布的厚尾性,同时将三步重要抽样技术发展到基多元t-Copula分布的资产组合模型中,拓宽和丰富了信用资产组合风险度量模型.同时,并运用了非线性优化技术中的Levenberg-Marquardt算法来解决重要抽样技术中风险因子期望向量估计.模拟结果表明该算法比普通Monte Carlo模拟法的计算效率更有效,且能很大程度上减少所要估计的损失概率的方差,从而更精确地估计出信用投资组合损失分布的尾部概率或给定置信度下组合VaR值.

引用

页码：46 / 55

页数：10

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