Increasing the number of inner replications of multifactor portfolio credit risk simulation in the t-copula model

Abstract

We consider the problem of simulating tail loss probabilities and expected losses conditioned on exceeding a large threshold (expected shortfall) for credit portfolios. Instead of the commonly used normal copula framework for the dependence structure between obligors, we use the t-copula model. We increase the number of inner replications using the so-called geometric shortcut idea to increase the efficiency of the simulations. The paper contains all details for simulating the risk of the t-copula credit risk model by combining outer importance sampling (IS) with the geometric shortcut. Numerical results show that the applied method is efficient in assessing tail loss probabilities and expected shortfalls for credit risk portfolios. We also compare the tail loss probabilities and expected shortfalls under the normal and t-copula model.