Credit Migration Risk and Point in Time Credit Dynamics: A New Perspective for Credit Risk Management

Abstract

This paper presents a credit migration model that aims to consistently capture the point-in-time dynamics of the credit worthiness of debt issuers and their obligations, and a calibration routine that permits the model to effectively fit historical ratings data. Our approach is to view the rating migration matrices as the operator semi-group associated to an approximated parametric infinitesimal generators. Our credit model accounts not only for default risk dynamics but also for the entire transition among states of the rating migration matrix. This modeling feature is fundamental for an efficient risk management of credit derivatives and credit risk portfolios conditionally on a state of the economy or specific macro factors. We fit our model to the historical average rating migration matrices published by Moody’s Investors Service, focusing on the banking sector over the period 1920-2005. Our results show that the model can identify the through-the-cycle transition across rating scales and that the point-in-time migration probabilities are only generated by stressed economic conditions and can only be justified by the influence of macro factors on the through-the-cycle unconditional probability values. The great level of modeling details and the accuracy of the produced results is an improvement over those of other available models.