Credit rating dynamics in the presence of unknown structural breaks |
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Authors: | Haipeng Xing Ning Sun |
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Institution: | a Department of Applied Mathematics and Statistics, State University of New York at Stony Brook, Stony Brook, NY 11794, United States b MEAG New York Corporation, 540 Madison Avenue, New York, NY 10022, United States |
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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. |
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Keywords: | C13 C41 G12 G20 |
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