统计研究 ›› 2008, Vol. 25 ›› Issue (11): 73-78.

• 论文 • 上一篇    下一篇

基于连接函数的 整合风险度量研究

侯成琪 王频   

  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-11-15 发布日期:2008-11-15

A Study of Integrated Risk Measurement Based on Copula

Hou Chengqi & Wang Pin   

  • Received:1900-01-01 Revised:1900-01-01 Online:2008-11-15 Published:2008-11-15

摘要: 本文利用连接函数(Copula)解决整合风险管理中不同类型风险的联合分布建模问题,提出了基于连接函数的整合风险度量Copula-VaR及其蒙特卡洛模拟算法;以深圳发展银行和上海浦东发展银行为研究对象,将Copula-VaR与N-VaR和Add-VaR这两种业界常用的近似整合风险度量方法进行了实证比较分析,发现:与Copula-VaR相比,N-VaR和Add-VaR存在高估风险的倾向,而其主要原因则是由于N-VaR和Add-VaR对信用收益率与市场收益率之间的相关结构进行了不符合实际的假设。

关键词: 整合风险度量, 联合分布, VaR, 连接函数

Abstract: This article uses Copula to solve the problem of joint distribution modeling of variant risks in integrated risk management, puts forward a method of integrated risk measurement based on Copula: Copula-VaR and its Monte Carlo simulation algorithm. Using Shenzhen Development Bank and Shanghai Pudong Development Bank as research objects, this article compares Copula-VaR with approximate integrated risk measurements N-VaR and Add-VaR, finds that N-VaR and Add-VaR tend to overestimate risk and the main reason is that they do reasonless assumption about correlation structure between credit return and market return.

 

Key words: Integrated risk measurement, Joint distribution, VaR, Copula