An improved multivariate Markov chain model for credit risk

In this paper we use Ching's multivariate Markov chain model to model the dependency of rating transitions of several credit entities. The model is an enhancement of the multivariate Markov chain model for ratings considered by Siu et al. Our model is more parsimonious, flexible and empirically...

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Bibliographic Details
Published in:Journal of credit risk 2009-12, Vol.5 (4), p.83-106
Main Authors: Ching, Wai-Ki, Siu, Tak-Kuen, Li, Li-min, Jiang, Hao, Li, Tang
Format: Article
Language:English
Subjects:
Credit ratings
Credit risk
Linear programming
Markov analysis
Parameter estimation
Studies
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Summary:In this paper we use Ching's multivariate Markov chain model to model the dependency of rating transitions of several credit entities. The model is an enhancement of the multivariate Markov chain model for ratings considered by Siu et al. Our model is more parsimonious, flexible and empirically competent than the model used by Siu et al. We adopt an efficient method to calibrate the model parameters and formulate the estimation problem as a linear programming problem that can easily be solved using spreadsheets. We compare the estimation results and the computational efficiency of the enhanced model with that of Siu et al. We also empirically investigate the effect of incorporating both positive and negative associations on portfolio credit risks. [PUBLICATION ABSTRACT]
ISSN:1744-6619
1744-6619
DOI:10.21314/JCR.2009.102