Importance sampling method for portfolio risk

被引：0

作者：

Xu, Chenglong ^{[1
,2
]}

Wu, Qian ^{[1
]}

Sun, Lihua ^{[3
]}

机构：

[1] Department of Mathematics, Tongji University, Shanghai

[2] Shanghai E-Institute of Scientific Computing and Shanghai Key Laboratory of Scientific Computing, Shanghai Normal University, Shanghai

[3] School of Economics and Management, Tongji University, Shanghai

来源：

Tongji Daxue Xuebao/Journal of Tongji University | 2015年 / 43卷 / 04期

关键词：

Gaussian Copula model; Importance sampling; Monte Carlo simulation; Portfolio risk;

D O I：

10.11908/j.issn.0253-374x.2015.04.022

中图分类号：

学科分类号：

摘要：

Based on the Gaussian Copula model with arbitrary marginal distribution in portfolio's market risk or credit risk; To improve the efficiency in Monte Carlo simulation with importance sampling, we first transform loss to a function of a high-dimensional normal vector, then the Newton's method and a method based on the large deviation theory are used to estimate the coefficients in measure transformation, and the method of freezing coefficient is also proposed. Numerical experiments show that compared with standard Monte Carlo method, the algorithm proposed in the paper reduce simulation error greatly and therefore improve computational efficiency. ©, 2015, Science Press. All right reserved.

引用

页码：633 / 638

页数：5

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