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The ordered qualitative model for credit rating transitions

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  • Feng, D.
  • Gourieroux, C.
  • Jasiak, J.

Abstract

Information on the expected changes in credit quality of obligors is contained in credit migration matrices which trace out the movements of firms across ratings categories in a given period of time and in a given group of bond issuers. The rating matrices provided by Moody’s, Standard &Poor’s and Fitch became crucial inputs to many applications, including the assessment of risk on corporate credit portfolios (CreditVar) and credit derivatives pricing. We propose a factor probit model for modeling and prediction of credit rating matrices that are assumed to be stochastic and driven by a latent factor. The filtered latent factor path reveals the effect of the economic cycle on corporate credit ratings, and provides evidence in support of the PIT (point-in-time) rating philosophy. The factor probit model also yields the estimates of cross-sectional correlations in rating transitions that are documented empirically but not fully accounted for in the literature and in the regulatory rules established by the Basle Committee.
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  • Feng, D. & Gourieroux, C. & Jasiak, J., 2008. "The ordered qualitative model for credit rating transitions," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 111-130, January.
  • Handle: RePEc:eee:empfin:v:15:y:2008:i:1:p:111-130
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    References listed on IDEAS

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    Cited by:

    1. Alain Monfort & Jean-Paul Renne, 2013. "Default, Liquidity, and Crises: an Econometric Framework," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 11(2), pages 221-262, March.
    2. Chateau, Jean-Pierre D., 2011. "Contribution à la réglementation de Bâle-3 : de la consistance interne du continuum du crédit commercial en marquant à la « valeur de modèle » le risque de crédit des engagements de crédit," L'Actualité Economique, Société Canadienne de Science Economique, vol. 87(4), pages 445-479, décembre.
    3. Guglielmo Maria Caporale & Roman Matousek & Chris Stewart, 2011. "EU Banks Rating Assignments: Is There Heterogeneity between New and Old Member Countries?," Review of International Economics, Wiley Blackwell, vol. 19(1), pages 189-206, February.
    4. Caporale, Guglielmo Maria & Matousek, Roman & Stewart, Chris, 2012. "Ratings assignments: Lessons from international banks," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1593-1606.
    5. Forster, Jonathan J. & Buzzacchi, Matteo & Sudjianto, Agus & Nagao, Risa, 2016. "Modelling credit grade migration in large portfolios using cumulative t-link transition models," European Journal of Operational Research, Elsevier, vol. 254(3), pages 977-984.
    6. Irina Peaucelle, 2005. "Dynamic analysis of bankruptcy and economic waves," PSE Working Papers halshs-00590851, HAL.
    7. Gourieroux, C. & Monfort, A., 2008. "Quadratic stochastic intensity and prospective mortality tables," Insurance: Mathematics and Economics, Elsevier, vol. 43(1), pages 174-184, August.
    8. Anisa Caja & Quentin Guibert & Frédéric Planchet, 2015. "Influence of Economic Factors on the Credit Rating Transitions and Defaults of Credit Insurance Business," Working Papers hal-01178812, HAL.
    9. Areski Cousin & Mohamed Reda Kheliouen, 2016. "A comparative study on the estimation of factor migration models," Working Papers halshs-01351926, HAL.
    10. 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.
    11. Chan, Ngai Hang & Wong, Hoi Ying & Zhao, Jing, 2012. "Structural model of credit migration," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3477-3490.
    12. Hwang, Ruey-Ching & Chung, Huimin & Chu, C.K., 2010. "Predicting issuer credit ratings using a semiparametric method," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 120-137, January.
    13. Adrian Gepp & Kuldeep Kumar & Sukanto Bhattacharya, 2010. "Business failure prediction using decision trees," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(6), pages 536-555.
    14. Alexander B. Matthies, 2013. "Empirical Research on Corporate Credit-Ratings: A Literature Review," SFB 649 Discussion Papers SFB649DP2013-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Alexander Karminsky, 2016. "Rating models: emerging market distinctions," Papers 1607.02422, arXiv.org.
    16. Chateau, John-Peter D., 2009. "Marking-to-model credit and operational risks of loan commitments: A Basel-2 advanced internal ratings-based approach," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 260-270, December.
    17. Mariusz Górajski & Dobromił Serwa & Zuzanna Wośko, 2016. "Measuring expected time to default under stress conditions for corporate loans," NBP Working Papers 237, Narodowy Bank Polski, Economic Research Department.
    18. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 2(1), pages 1-22, March.
    19. Balios, Dimitris & Thomadakis, Stavros & Tsipouri, Lena, 2016. "Credit rating model development: An ordered analysis based on accounting data," Research in International Business and Finance, Elsevier, vol. 38(C), pages 122-136.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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