Stochastic Migration Models with Application to Corporate Risk

Posted: 29 Feb 2008

See all articles by Christian Gourieroux

Christian Gourieroux

University of Toronto - Department of Economics; Center for Interuniversity Research and Analysis on Organization (CIRANO); Ecole Nationale de la Statistique et de l'Administration Economique (ENSAE); National Bureau of Economic Research (NBER)

Patrick Gagliardini

USI Università della Svizzera italiana; Swiss Finance Institute

Multiple version iconThere are 2 versions of this paper

Date Written: 2005

Abstract

In this article we explain how to use rating histories provided by the internal scoring systems of banks and rating agencies in order to predict the future risk of a set of borrowers. The method is developed following the steps suggested by the Basle Committee. To introduce both migration correlation and non-Markovian serial dependence, we consider rating histories with stochastic transition matrices. We develop the methodology to estimate both the number and dynamics of the factors influencing the transitions and we explain how to use the model for prediction. As an illustration, the ordered probit model with unobservable dynamic factor is estimated from French data on corporate risk.

Keywords: credit risk, Jacobi process, Kalman filter, migration correlation, rating, stochastic intensity

Suggested Citation

Gourieroux, Christian and Gagliardini, Patrick, Stochastic Migration Models with Application to Corporate Risk ( 2005). Journal of Financial Econometrics, Vol. 3, Issue 2, pp. 188-226, 2005. Available at SSRN: https://ssrn.com/abstract=821748

Christian Gourieroux (Contact Author)

University of Toronto - Department of Economics ( email )

150 St. George Street
Toronto, Ontario M5S 3G7
Canada
416-978-4349 (Phone)
416-978-6713 (Fax)

Center for Interuniversity Research and Analysis on Organization (CIRANO) ( email )

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Montreal, Quebec H3C 3J7
Canada

Ecole Nationale de la Statistique et de l'Administration Economique (ENSAE) ( email )

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France
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National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
United States

Patrick Gagliardini

USI Università della Svizzera italiana ( email )

Via Buffi 13
Lugano, TN 6900
Switzerland

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

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