Article ID Journal Published Year Pages File Type
5099785 Journal of Economic Dynamics and Control 2008 13 Pages PDF
Abstract
This paper presents a hidden Markov model of credit quality dynamics, and highlights the use of filtering-based estimation methods for models of this kind. We suppose that the Markov chain governing the 'true' credit quality evolution is hidden in 'noisy' or incomplete observations represented by posted credit ratings. Parameters of the model, namely credit transition probabilities, are estimated using the EM algorithm. Filtering methods provide recursive updates of optimal estimates so the model is 'self-calibrating'. The estimation procedure is illustrated with an application to a data set of Standard & Poor's credit ratings.
Related Topics
Physical Sciences and Engineering Mathematics Control and Optimization
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