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A coupled Markov chain approach to credit risk modeling

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  • Wozabal, David
  • Hochreiter, Ronald

Abstract

We propose a Markov chain model for credit rating changes. We do not use any distributional assumptions on the asset values of the rated companies but directly model the rating transitions process. The parameters of the model are estimated by a maximum likelihood approach using historical rating transitions and heuristic global optimization techniques.

Suggested Citation

  • Wozabal, David & Hochreiter, Ronald, 2012. "A coupled Markov chain approach to credit risk modeling," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 403-415.
    • Handle: RePEc:eee:dyncon:v:36:y:2012:i:3:p:403-415
    DOI: 10.1016/j.jedc.2011.09.011
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    18. Stefan Weber & Kay Giesecke, 2003. "Credit Contagion and Aggregate Losses," Computing in Economics and Finance 2003 246, Society for Computational Economics.
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    Cited by:

    1. Li, Yibei & Wang, Ximei & Djehiche, Boualem & Hu, Xiaoming, 2020. "Credit scoring by incorporating dynamic networked information," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1103-1112.
    2. D. V. Boreiko & Y. M. Kaniovski & G. Ch. Pflug, 2016. "Modeling dependent credit rating transitions: a comparison of coupling schemes and empirical evidence," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(4), pages 989-1007, December.
    3. R. Dolzhenko A. & Р. Долженко А., 2018. "Ключевые Показатели Эффективности Работы С Проблемными Активами Банка И Их Расчет // Key Performance Indicators Of The Bank’S Distressed Assets And Their Calculation," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(4), pages 130-145.
    4. Tamás Kristóf, 2021. "Sovereign Default Forecasting in the Era of the COVID-19 Crisis," JRFM, MDPI, vol. 14(10), pages 1-24, October.
    5. W. Hölzl & S. Kaniovski & Y. Kaniovski, 2019. "Exploring the dynamics of business survey data using Markov models," Computational Management Science, Springer, vol. 16(4), pages 621-649, October.
    6. T. Gärtner & S. Kaniovski & Y. Kaniovski, 2021. "Numerical estimates of risk factors contingent on credit ratings," Computational Management Science, Springer, vol. 18(4), pages 563-589, October.
    7. David Conaly Martínez Vázquez & Christian Bucio Pacheco & Alejandra Cabello Rosales, 2021. "Proyección Markoviana para 2020 y 2021 de las Calificaciones Corporativas en México," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(1), pages 1-21, Enero - M.
    8. D. V. Boreiko & Y. M. Kaniovski & G. Ch. Pflug, 2017. "Numerical Modeling of Dependent Credit Rating Transitions with Asynchronously Moving Industries," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 499-516, March.
    9. Dmitri Boreiko & Serguei Kaniovski & Yuri Kaniovski & Georg Ch. Pflug, 2018. "Business Cycles and Conditional Credit-Rating Migration Matrices," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 1-19, December.
    10. David Conaly Martínez Vázquez & Christian Bucio Pacheco & Alejandra Cabello Rosales, 2021. "Proyección Markoviana para 2020 y 2021 de las Calificaciones Corporativas en México," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(1), pages 1-21, Enero - M.

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    More about this item

    Keywords

    Credit risk; Markov models; Ratings; Conditional value-at-risk; Bond portfolios;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G01 - Financial Economics - - General - - - Financial Crises
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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