Tail approximation for credit risk portfolios with heavy-tailed risk factors

Krassimir Kostadinov

Abstract

ABSTRACT

We consider a portfolio credit risk model in the spirit of CreditMetrics. The multivariate normally distributed underlying risk factors in that model are replaced by more general multivariate elliptical factors with heavy-tailed marginals, introducing tail-dependence. We consider a full-scale version of the model, in which we incorporate not only the default risk but also rating migrations, credit spread volatility and recovery risk. We derive an upper bound of the portfolio loss distribution, which is particularly accurate at high loss levels. Given the complexity of our model, we obtain this result using a mixture of analytic techniques and Monte Carlo simulation. An approximation of VAR and a new method to determine the contributions of the individual credits to the overall portfolio risk is suggested.