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Journal of Banking & Finance Vol. 36 No. 1 2012

Credit rating dynamics in the presence of unknown structural breaks

Haipeng Xing1,2; Ning Sun2,1; Ying Chen3

1 State University of New York · 2 Stony Brook University · 3 MEAG New York Corporation, 540 Madison Avenue, New York, NY 10022, United States

Abstract

In many credit risk and pricing applications, credit transition matrix is modeled by a constant transition probability or generator matrix for Markov processes. Based on empirical evidence, we model rating transition processes as piecewise homogeneous Markov chains with unobserved structural breaks. The proposed model provides explicit formulas for the posterior distribution of the time-varying rating transition generator matrices, the probability of structural break at each period and prediction of transition matrices in the presence of possible structural breaks. Estimating the model by credit rating history, we show that the structural break in rating transitions can be captured by the proposed model. We also show that structural breaks in rating dynamics are different for different industries. We then compare the prediction performance of the proposed and time-homogeneous Markov chain models.

DOI
10.1016/j.jbankfin.2011.06.005
Volume
36
Issue
1
Pages
78-89
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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