Abstract
We consider portfolio credit risk modeling with a focus on two approaches, the factor model, and the copula model. While other models have received greater scrutiny, both factor and cupola models have received little attention although these are appropriate for rating-based portfolio risk analysis. We review the two models with emphasis on the joint default probability. The copula function describes the dependence structure of a multivariate random variable. In this paper, it is used as a practical to simulation of generate portfolio with different copula, we only use Gaussian and t-copula case. And we generate portfolio default distributions and study the sensitivity of commonly used risk measures with respect to the approach in modeling the dependence structure of the portfolio.
Highlights
There is a need to understand components of portfolio risk and their interaction
Several portfolio credit risk models developed in the industry have been made public since
We generated portfolio default distributions and studied the sensitivity of commonly used risk measures with respect to the approaches in modeling the dependence structure of the portfolio using as a rating-based approach using cupola mathematics
Summary
There is a need to understand components of portfolio risk and their interaction. The Basel Committee for Banking Supervision in its Basel proposed (BIS, 2001) to develop an appropriate framework for a global financial regulation system. Several portfolio credit risk models developed in the industry have been made public since . Examples are: CreditMetrics (Gupton et al, 1997), CreditRisk+ (Credit Suisse Financial Products, 1997) and Credit Portfolio View (Wilson 1997a; 1997b). Others systems remain proprietary, such as KMV’s Portfolio Manager (Kealhofer, 1996). The models appear quite different on the surface, recent
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