Credit Rating Dynamics and Markov Mixture Models

25 Pages Posted: 5 Nov 2008

See all articles by Halina Frydman

Halina Frydman

New York University (NYU) - Department of Information, Operations, and Management Sciences

Til Schuermann

Oliver Wyman

Multiple version iconThere are 3 versions of this paper

Date Written: July 2004

Abstract

Despite overwhelming evidence to the contrary, credit migration matrices, used in many credit risk and pricing applications, are typically assumed to be generated by a simple Markov process. In this paper we propose a parsimonious model that is a mixture of (two) Markov chains. We estimate this model using credit rating histories and show that the mixture model statistically dominates the simple Markov model and that the differences between two models can be economically meaningful. The non-Markov property of our model implies that the future distribution of a firm's ratings depends not only on its current rating but also on its past rating history. Indeed we find that two firms with identical credit ratings can have substantially different transition probability vectors.

Keywords: Risk management, credit risk, credit derivatives

Suggested Citation

Frydman, Halina and Schuermann, Til, Credit Rating Dynamics and Markov Mixture Models (July 2004). NYU Working Paper No. S-CDM-04-08. Available at SSRN: https://ssrn.com/abstract=1295761

Halina Frydman (Contact Author)

New York University (NYU) - Department of Information, Operations, and Management Sciences ( email )

44 West Fourth Street
New York, NY 10012
United States
212-998-0453 (Phone)

Til Schuermann

Oliver Wyman ( email )

1166 6th Avenue
New York City, NY
United States

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