The ordered qualitative model for credit rating transitions |
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Authors: | D. Feng C. Gourieroux J. Jasiak |
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Affiliation: | 1. CIBC, Toronto, Canada;2. CEPREMAP, CREST and University of Toronto, Toronto, Canada;3. Department of Economics, York University, 4700 Keele Street, Toronto, ON, Canada M3J 1P3 |
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Abstract: | Information on the expected changes in credit quality of obligors is contained in credit migration matrices which trace out the movements of firms across ratings categories in a given period of time and in a given group of bond issuers. The rating matrices provided by Moody's, Standard & Poor's and Fitch became crucial inputs to many applications, including the assessment of risk on corporate credit portfolios (CreditVar) and credit derivatives pricing. We propose a factor probit model for modeling and prediction of credit rating matrices that are assumed to be stochastic and driven by a latent factor. The filtered latent factor path reveals the effect of the economic cycle on corporate credit ratings, and provides evidence in support of the PIT (point-in-time) rating philosophy. The factor probit model also yields the estimates of cross-sectional correlations in rating transitions that are documented empirically but not fully accounted for in the literature and in the regulatory rules established by the Basle Committee. |
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