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Stochastic Migration Models with Application to Corporate Risk

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  • Patrick Gagliardini

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. Copyright 2005, Oxford University Press.

Suggested Citation

  • Patrick Gagliardini, 2005. "Stochastic Migration Models with Application to Corporate Risk," Journal of Financial Econometrics, Oxford University Press, vol. 3(2), pages 188-226.
    • Handle: RePEc:oup:jfinec:v:3:y:2005:i:2:p:188-226
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbi013
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    Cited by:

    1. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    2. McNeil, Alexander J. & Wendin, Jonathan P., 2007. "Bayesian inference for generalized linear mixed models of portfolio credit risk," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 131-149, March.
    3. Alain Monfort & Jean-Paul Renne, 2013. "Default, Liquidity, and Crises: an Econometric Framework," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 221-262, March.
    4. Patrick Gagliardini & Christian Gouriéroux, 2011. "Approximate Derivative Pricing for Large Classes of Homogeneous Assets with Systematic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 237-280, Spring.
    5. Parrini, Alessandro, 2013. "Importance Sampling for Portfolio Credit Risk in Factor Copula Models," MPRA Paper 103745, University Library of Munich, Germany.
    6. Christian Gouriéroux & Alain Monfort, 2017. "Composite Indirect Inference with Application," Working Papers 2017-07, Center for Research in Economics and Statistics.
    7. Jian He & Asma Khedher & Peter Spreij, 2024. "Calibration of the rating transition model for high and low default portfolios," Papers 2405.00576, arXiv.org.
    8. Anand Deo & Sandeep Juneja, 2021. "Credit Risk: Simple Closed-Form Approximate Maximum Likelihood Estimator," Operations Research, INFORMS, vol. 69(2), pages 361-379, March.
    9. Myriam Ben Ayed & Adel Karaa & Jean‐Luc Prigent, 2018. "Duration Models For Credit Rating Migration: Evidence From The Financial Crisis," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1870-1886, July.
    10. Monica Billio & Roberto Casarin, 2010. "Bayesian Estimation of Stochastic-Transition Markov-Switching Models for Business Cycle Analysis," Working Papers 1002, University of Brescia, Department of Economics.
    11. Areski Cousin & Jérôme Lelong & Tom Picard, 2022. "Rating transitions forecasting: a filtering approach," Working Papers hal-03347521, HAL.
    12. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    13. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Areski Cousin & J'er^ome Lelong & Tom Picard, 2021. "Rating transitions forecasting: a filtering approach," Papers 2109.10567, arXiv.org, revised Jun 2023.
    15. Djeundje, Viani Biatat & Crook, Jonathan, 2018. "Incorporating heterogeneity and macroeconomic variables into multi-state delinquency models for credit cards," European Journal of Operational Research, Elsevier, vol. 271(2), pages 697-709.
    16. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    17. Andre Lucas & Bastiaan Verhoef, 2012. "Aggregating Credit and Market Risk: The Impact of Model Specification," Tinbergen Institute Discussion Papers 12-057/2/DSF36, Tinbergen Institute.
    18. Areski Cousin & Mohamed Reda Kheliouen, 2016. "A comparative study on the estimation of factor migration models," Working Papers halshs-01351926, HAL.
    19. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    20. Gourieroux, C. & Monfort, A., 2018. "Composite indirect inference with application to corporate risks," Econometrics and Statistics, Elsevier, vol. 7(C), pages 30-45.
    21. Areski Cousin & Jérôme Lelong & Tom Picard, 2023. "Rating transitions forecasting: a filtering approach," Post-Print hal-03347521, HAL.
    22. Anand Deo & Sandeep Juneja, 2019. "Credit Risk: Simple Closed Form Approximate Maximum Likelihood Estimator," Papers 1912.12611, arXiv.org.
    23. Gourieroux, C. & Jasiak, J., 2012. "Granularity adjustment for default risk factor model with cohorts," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1464-1477.
    24. Stefanescu, Catalina & Tunaru, Radu & Turnbull, Stuart, 2009. "The credit rating process and estimation of transition probabilities: A Bayesian approach," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 216-234, March.
    25. Monica Billio & Roberto Casarin, 2008. "Identifying Business Cycle Turning Points with Sequential Monte Carlo Methods," Working Papers 0815, University of Brescia, Department of Economics.

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