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Approaches to Default Probability Estimation of Credit Rating Agencies' Rating Scales

Author

Listed:
  • Sergey Kutenko

    (ACRA (JSC) Methodology Group)

  • Kirill Ozerov

    (HSE University, ACRA (JSC) Validation Squad)

Abstract

Under limited data, the classical cohort method for the creation of migration matrices does not fully reflect the dynamics of the credit quality of the objects within the sample. This problem is exacerbated for objects of lower credit quality less represented in the sample. This paper investigates a continuous time approach to the creation of migration matrices. A continuous time migration matrix considers migrations between the credit quality of objects on a given horizon on a daily basis, and thus not only the initial state of the default object, but also its movement between credit quality categories up to the moment of default. We demonstrate that the classical cohort method is inferior to the continuous time method both on simulated data and in the analysis of the real migration statistics of the credit ratings of Russian companies. The cohort method overestimates the probability of default across the entire credit rating scale. The continuous time method consistently surpasses the cohort method in accuracy and efficiency starting from the second year of observations and allows the mitigation of the problem of data scarcity.

Suggested Citation

  • Sergey Kutenko & Kirill Ozerov, 2024. "Approaches to Default Probability Estimation of Credit Rating Agencies' Rating Scales," Russian Journal of Money and Finance, Bank of Russia, vol. 83(4), pages 98-118, December.
    • Handle: RePEc:bkr:journl:v:83:y:2024:i:4:p:98-118
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    References listed on IDEAS

    as
    1. Jafry, Yusuf & Schuermann, Til, 2004. "Measurement, estimation and comparison of credit migration matrices," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2603-2639, November.
    2. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
    3. Hanson, Samuel & Schuermann, Til, 2006. "Confidence intervals for probabilities of default," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2281-2301, August.
    4. Robert A. Jarrow & David Lando & Stuart M. Turnbull, 2008. "A Markov Model for the Term Structure of Credit Risk Spreads," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 18, pages 411-453, World Scientific Publishing Co. Pte. Ltd..
    5. Lando, David & Skodeberg, Torben M., 2002. "Analyzing rating transitions and rating drift with continuous observations," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 423-444, March.
    6. Christensen, Jens H.E. & Hansen, Ernst & Lando, David, 2004. "Confidence sets for continuous-time rating transition probabilities," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2575-2602, November.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    credit risk modelling; migration matrix; probability of default; credit ratings;
    All these keywords.

    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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