Empirical Performance of LGD Prediction Models

Abstract

The Global Financial Crisis highlighted that default and recovery rates of multiple borrowers generally deteriorate jointly during economic downturns. The vast majority of the literature, as well as many industry credit portfolio risk models ignore this and analyze default probabilities and recoveries in the event of default separately. As a result, the models project losses which are too low in economic downturns such as the recent financial crisis. Nevertheless, alternatives of incorporating the dependence between probabilities of default and recovery rates have been proposed. This paper is the first of its kind to assess the performance of these structurally different approaches. Four banks using different estimation procedures are compared. We use RMSE and RAE to measure the predictive accuracy of each procedure. The results show, that indeed models accounting for the correlation of default and recovery perform better than models ignoring it.