Copula模型的改进及其应用  

Improvement and Application of Copula Model

作　　者：夏喆[1] 余浪 黄洁莉[2] Xia Zhe;Yu Lang;Huang Jieli(School of Accounting,Hubei University of Economics,Wuhan 430205,China;School of Accounting,Zhongnan University of Economics and Law,Wuhan 430070,China)

机构地区：[1]湖北经济学院会计学院,武汉430205 [2]中南财经政法大学会计学院,武汉430070

出　　处：《统计与决策》2024年第10期58-62,共5页Statistics & Decision

基　　金：教育部人文社会科学研究基金项目(18YJC630203)。

摘　　要：Copula模型能精确计算投资组合尾部风险,弥补Person相关系数的不足。文章基于信用风险Cop⁃ula模型,探讨了不同抽样算法在信贷投资组合中的应用问题,优化重要性抽样和交叉熵算法,测试了高斯及t-Copula模型的风险计算算法,并通过数值模拟予以检验,结果表明:朴素蒙特卡罗模拟的精度和效率较低;重要性抽样算法通过解析逼近显著降低计算方差,提高精度,但求解复杂且耗时;交叉熵算法同样有效,但需自适应算法求解优化问题。算例分析结果表明,基于不同场景选择Copula模型,可提高信贷投资组合风险计算精度和效率。Copula models can be used to accurately calculate the tail risk of investment portfolios and compensate for the shortcomings of Person correlation coefficient.Based on the credit risk Copula model,this paper discusses the application of dif-ferent sampling algorithms in credit portfolios,optimizes importance sampling and cross-entropy algorithms,tests the risk calcula-tion algorithms of Gaussian and t-Copula models,and verifies them through numerical simulation.The results are shown as fol-lows:The precision and efficiency of naive Monte Carlo simulation are low.The importance sampling algorithm significantly reduc-es the calculation variance and improves accuracy through analytical approximation,but the solution is complex and time-con-suming.The cross-entropy algorithm is also effective,but it requires adaptive algorithms to solve optimization problems.The ex-ample shows that selecting Copula models based on different scenarios can improve the calculation accuracy and efficiency of credit portfolio risks.

关 键 词：投资组合 风险分析 COPULA模型 

分 类 号：F832.48[经济管理—金融学]