Abstract:
Default probabilities and recovery rate densities are not constant over the credit cycle; yet many models assume that they are. This paper proposes and estimates a model in which these two variables depend on an unobserved credit cycle, modelled by a twostate Markov chain. The proposed model is shown to produce a better fit to observed recoveries than a standard static approach. The model indicates that ignoring the dynamic nature of credit risk could lead to a severe underestimation of e.g. the 95% VaR, such that the actual VaR could be higher by a factor of up to 1.7. Also, the model indicates that the credit cycle is related to but distinct from the business cycle as e.g. determined by the NBER, which might explain why previous studies have found the power of macroeconomic variables in explaining default probabilities and recoveries to be low.