非正态数据下商业银行信用风险和经济资本度量  

Measuring credit risk and economic capital for commercial banks under non-Gaussian data

作　　者：慕文涛[1] 陈典发[1] 陈冀[1] 

机构地区：[1]南开大学经济学院金融系,天津300071

出　　处：《系统工程理论与实践》2013年第6期1372-1379,共8页Systems Engineering-Theory & Practice

基　　金：教育部科学技术研究重大项目"金融信用风险的量化研究"(309009)

摘　　要：信用风险和经济资本度量是商业银行风险管理最重要的目标之一.通过使用Johnson变换解决非正态数据情况下经济资本的计算问题,克服以往研究中在Copula方法下进行Monte Carlo模拟时对正态或t分布要求的局限性.将实际数据转换为标准正态分布.非常方便地使用MonteCarlo模拟度量违约时间和计算经济资本.研究结果表明,基于Johnson变换下的Copula方法可行而且合理,该研究为我国商业银行在《巴塞尔新资本协议》(BeselⅡ)下进行有效的风险管理提供一些参考和新的思路.Measuring the credit risk and economic capital is one of the most important aims in risk management for commercial banks. The authors use Johnson transformation to solve the problem of economic capital under non-Gaussian data. By transforming real data to standard normal distribution, the authors overcome the restricts of Monte Carlo simulation in Copula method, which often requires the Gaussian or t distribution. It is convenient to simulate the correlated default time and the economic capital for banks. From the comparative analysis, the Johnson transformation is feasible and reasonable. This paper provides an effective quantitative method in risk management for commercial banks under ＂Basel Capital Accord＂ （Basel II） and the algorithm has a certain reference.

关 键 词：信用风险 COPULA函数 Johnson变换 MONTE CARLO模拟 经济资本 

分 类 号：F830.33[经济管理—金融学]