Credit Rating Dynamics and Markov Mixture Models

Journal of Banking and Finance, Forthcoming

Wharton Financial Institutions Center Working Paper No. 04-15

Posted: 18 Jul 2009

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

Abstract

Despite mounting 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. Based on empirical evidence we propose a parsimonious model that is a mixture of (two) Markov chains, where the mixing is on the speed of movement among credit ratings. 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 current credit ratings can have substantially different transition probability vectors. We also find that conditioning on the state of the business cycle or industry group does not remove the heterogeneity with respect to the rate of movement. We go on to compare the performance of mixture and Markov chain using out-of sample predictions.

Keywords: Risk management, credit risk, credit derivatives

JEL Classification: C13, C41, G12, G20

Suggested Citation

Frydman, Halina and Schuermann, Til, Credit Rating Dynamics and Markov Mixture Models. Journal of Banking and Finance, Forthcoming; Wharton Financial Institutions Center Working Paper No. 04-15. Available at SSRN: https://ssrn.com/abstract=1011928

Halina Frydman

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 (Contact Author)

Oliver Wyman ( email )

1166 6th Avenue
New York City, NY
United States

Register to save articles to
your library

Register

Paper statistics

Abstract Views
643
PlumX Metrics
!

Under construction: SSRN citations while be offline until July when we will launch a brand new and improved citations service, check here for more details.

For more information