Copula-based factor model for credit risk analysis

A standard quantitative method to assess credit risk employs a factor model based on joint multivariate normal distribution properties. By extending the one-factor Gaussian copula model to produce a more accurate default forecast, this paper proposes the incorporation of a state-dependent recovery rate into the conditional factor loading and to model them sharing a unique common factor. The common factor governs the default rate and recovery rate simultaneously, implicitly creating their association. In accordance with Basel III, this paper shows that the tendency toward default during a hectic period is governed more by systematic risk than by idiosyncratic risk. Among those considered, the model with random factor loading and a state-dependent recovery rate is shown to be superior in terms of default prediction.