Fast simulation for multifactor portfolio credit risk in the t-copula model

Authors:
Wanmo Kang;Perwez Shahabuddin
Affiliations:
Moody's KMV, New York, NY;Columbia University, New York, NY
Venue:
WSC '05 Proceedings of the 37th conference on Winter simulation
Year:
2005

Citing 1
Cited 2

An importance sampling method for portfolios of credit risky assets

WSC '04 Proceedings of the 36th conference on Winter simulation

Perwez Shahabuddin, 1962--2005: A professional appreciation

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Stochastic Root Finding and Efficient Estimation of Convex Risk Measures

Operations Research

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Abstract

We present an importance sampling procedure for the estimation of multifactor portfolio credit risk for the t-copula model, i.e, the case where the risk factors have the multivariate t distribution. We use a version of the multivariate t that can be expressed as a ratio of a multivariate normal and a scaled chi-square random variable. The procedure consists of two steps. First, using the large deviations result for the Gaussian model in Glasserman, Kang, and Shahabuddin (2005a), we devise and apply a change of measure to the chi-square random variable. Then, conditional on the chi-square random variable, we apply the importance sampling procedure developed for the Gaussian copula model in Glasserman, Kang, Shahabuddin (2005b). We support our importance sampling procedure by numerical examples.