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Predicting rating changes for banks: how accurate are accounting and stock market indicators?

Author

Listed:
  • Isabelle Distinguin

    (LAPE - Laboratoire d'Analyse et de Prospective Economique - GIO - Gouvernance des Institutions et des Organisations - UNILIM - Université de Limoges)

  • Iftekhar Hasan
  • Amine Tarazi

    (LAPE - Laboratoire d'Analyse et de Prospective Economique - GIO - Gouvernance des Institutions et des Organisations - UNILIM - Université de Limoges)

Abstract

We aim to assess how accurately accounting and stock market indicators predict rating changes for Asian banks. We conduct a stepwise process to determine the optimal set of early indicators by tracing upgrades and downgrades from rating agencies, as well as other relevant factors. Our results indicate that both accounting and market indicators are useful leading indicators but are more effective in predicting upgrades than downgrades, especially for large banks. Moreover, early indicators are only significant in predicting rating changes for banks that are more focused on traditional banking activities such as deposit and loan activities. Finally, a higher reliance of banks on subordinated debt is associated with better accuracy of early indicators.
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Suggested Citation

  • Isabelle Distinguin & Iftekhar Hasan & Amine Tarazi, 2013. "Predicting rating changes for banks: how accurate are accounting and stock market indicators?," Post-Print hal-00915682, HAL.
  • Handle: RePEc:hal:journl:hal-00915682
    DOI: 10.1007/s10436-012-0195-0
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    Cited by:

    1. Volkova, Olga (Волкова, Ольга) & Lvova, Irina (Львова, Ирина), 2016. "The bank's rating, the rating agencies, Basel II of, financial indicator, the econometric model [Влияние Финансовых Показателей На Международные Рейтинги Российских Банков]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 177-195, February.
    2. Alexander M. Karminsky & Ella Khromova, 2016. "Modelling banks’ credit ratings of international agencies," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 6(3), pages 341-363, December.
    3. Papanikolaou, Nikolaos I., 2018. "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, vol. 34(C), pages 61-85.
    4. Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    5. Aggarwal, Nidhi & Singh, Manish K. & Thomas, Susan, 2023. "Do decreases in Distance-to-Default predict rating downgrades?," Economic Modelling, Elsevier, vol. 129(C).
    6. Karminsky, A. & Dyachkova, N., 2020. "Empirical study of the relationship between credit cycles and changes in credit ratings," Journal of the New Economic Association, New Economic Association, vol. 48(4), pages 138-160.
    7. Guglielmo D’Amico, 2013. "A semi-Markov approach to the stock valuation problem," Annals of Finance, Springer, vol. 9(4), pages 589-610, November.
    8. Emna Damak, 2018. "CAMELS Model With a Proposed ¡®S¡¯ for the Bank Credit Risk Rating," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(9), pages 1-69, September.

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    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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