Stochastic migration models with application to corporate risk

Patrick Gagliardini, Christian Gouriéroux

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)188-226
Number of pages39
JournalJournal of Financial Econometrics
Volume3
Issue number2
DOIs
Publication statusPublished - 1 Mar 2005
Externally publishedYes

Keywords

  • Credit risk
  • Jacobi process
  • Kalman filter
  • Migration correlation
  • Rating stochastic intensity

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