Working Paper no. 133
By Pamela Nickell, William Perraudin and Simone Varotto
The distribution of ratings changes plays a crucial role in many credit risk models. As is well known, these distributions vary across time and different issuer types. Ignoring such dependencies may lead to inaccurate assessments of credit risk. In this paper, we quantify the dependence of ratings transition probabilities on the industry and domicile of the obligor, and on the stage of the business cycle. Employing ordered probit models, we identify the incremental impact of these factors. Our approach gives a clearer picture of which conditioning factors are important than is obtained by comparing transition matrices estimated from different sub-samples.