Abstract:
Default probabilities (PDs) and correlations play a crucial role in the New Basel Capital Accord. In commercial credit risk models they are an important constituent. Yet, modeling and estimation of PDs and correlations is still under active discussion. We show how the Basel II one factor model which is used to calibrate risk weights can be extended to a model for estimating PDs and correlations. The important advantage of this model is that it uses actual information about the point in time of the credit cycle. Thus, uncertainties about the parameters which are needed for Value-at-Risk calculations in portfolio models may be substantially reduced. First empirical evidence for the appropriateness of the models and underlying risk factors is given with S&P data.