Observation of historical default rates supports the idea that default events (and, more generally, all indicators of credit quality and transition) are correlated. Default correlations are caused by similar economic conditions and, within a sector, by industry-specific reasons. However, incorporating default correlation in any portfolio credit risk analysis is difficult because of the lack of ...

Copula functions have become standard practice for pricing multi-name credit derivatives. Marginal default distributions are often chosen by using a simple deterministic intensity function. It is wellknown that this approach only generates default time correlation and, apart from jumps due to default events, does not generate correlation between the conditional default intensities, or the condi...

This paper generalizes Moody's correlated binomial default distribution for homogeneous (exchangeable) credit portfolio, which is introduced by Witt, to the case of inhomogeneous portfolios. As inhomogeneous portfolios, we consider two cases. In the first case, we treat a portfolio whose assets have uniform default correlation and non-uniform default probabilities. We obtain the default probabi...

This paper studies the problem of default correlation. We first introduce a random variable called “timeuntil-default” to denote the survival time of each defaultable entity or financial instrument, and define the default correlation between two credit risks as the correlation coefficient between their survival times. Then we argue why a copula function approach should be used to specify the jo...

This paper studies the problem of default correlation. We first introduce a random variable called “timeuntil-default” to denote the survival time of each defaultable entity or financial instrument, and define the default correlation between two credit risks as the correlation coefficient between their survival times. Then we argue why a copula function approach should be used to specify the jo...

The credit derivatives market has experienced remarkable growth over the past decade. As such, there is a growing interest in tools for pricing of the most prominent credit derivative, the credit default swap (CDS). In this paper, we propose a heuristic algorithm for pricing of basket default swaps (BDS). For this purpose, genetic network programming (GNP), which is one of the recent evolutiona...

We consider counterparty risk for interest rate payoffs in presence of correlation between the default event and interest rates. The previous analysis of Brigo and Masetti (2006), assuming independence, is further extended to interest rate payoffs different from simple swap portfolios. A stochastic intensity model with possible jumps is adopted for the default event. We find that correlation be...

This paper aims to estimate the joint default probability under the structuralform model with a random environment; namely stochastic correlation. By means of a singular perturbation method, we obtain an asymptotic expansion of a two-name joint default probability under a fast mean-reverting stochastic correlation model. The leading order term in the expansion is a joint default probability wit...

We consider counterparty risk for Credit Default Swaps (CDS) in presence of correlation between default of the counterparty and default of the CDS reference credit. Our approach is innovative in that, besides default correlation, which was taken into account in earlier approaches, we also model credit spread volatility. Stochastic intensity models are adopted for the default events, and default...