基于CPV模型改进的信用风险宏观压力测试研究  

The Credit Risk Macro Stress Testing Research Based on Improved CPV Model

作　　者：曹麟[1] 彭建刚[1] 

机构地区：[1]湖南大学金融与统计学院金融管理研究中心,湖南长沙410079

出　　处：《湖南大学学报（自然科学版）》2013年第12期107-113,共7页Journal of Hunan University:Natural Sciences

基　　金：国家自然科学基金资助项目(71073048);教育部博士点基金博导类项目(20110161110023)

摘　　要：对CPV模型的残差相关性假设进行了调整,使压力情景生成模型和风险传导模型能分开处理,从而可采用偏最小二乘法对信用风险传导模型进行参数估计,避免了宏观经济因子因多重共线性不能进压力测试系统这一问题.通过似无关回归对情景生成模型参数进行估计,在信用风险传导模型含有宏观经济因子滞后项情况下,使用蒙特卡洛模拟方法进行压力情景生成.算例分析结果表明,本文提出的压力测试方法可有效地应用于银行业逆周期管理.The residual correlation assumption of the CPV model was adjusted,and then,the stress scenarios generation model and the risk conduction model can be handled separately.Therefore,the partial least square method can be used to estimate the parameters of credit risk conduction model,avoiding the problem that macroeconomic factors could not be contained in the stress testing system for multicollinearity.The parameters of stress scenarios generation model were estimated through seemly unrelated regression,and Monte Carlo simulation method was used for stress scenarios generation when there exist lagged terms of macroeconomic factor in credit risk conduction model.Case analysis results show that the proposed stress testing method can be effectively applied to banking reverse cycle management.

关 键 词：CPV模型 宏观压力测试 多重共线性 偏最小二乘法 蒙特卡洛模拟 

分 类 号：F830.2[经济管理—金融学]