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Ratings assignments: Lessons from international banks

Author

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  • Caporale, Guglielmo Maria
  • Matousek, Roman
  • Stewart, Chris

Abstract

This paper estimates ordered logit models for bank ratings which include a country index to capture country-specific variation. The empirical findings support the hypothesis that the individual international bank ratings assigned by Fitch Ratings are underpinned by fundamental quantitative financial analyses. Also, there is strong evidence of a country effect. Our model is shown to provide accurate predictions of bank ratings for the period prior to the 2007–2008 banking crisis based upon publicly available information. However, our results also suggest that quantitative models are unlikely to predict ratings with complete accuracy. Furthermore, we find that both quantitative models and rating agencies are likely to produce highly inaccurate predictions of ratings during periods of financial instability.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jimfin:v:31:y:2012:i:6:p:1593-1606
    DOI: 10.1016/j.jimonfin.2012.02.018
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Vincenzo D’Apice & Giovanni Ferri & Punziana Lacitignola, 2016. "Rating Performance and Bank Business Models: Is There a Change with the 2007–2009 Crisis?," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 2(3), pages 385-420, November.
    2. Kimmel, Randall K. & Thornton, John H. & Bennett, Sara E., 2016. "Can statistics-based early warning systems detect problem banks before markets?," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 190-216.
    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. Giovanni Ferri & Panu Kalmi & Eeva Kerola, 2014. "Organizational Structure and Exposure to Crisis among European Banks: Evidence from Rating Changes," Journal of Entrepreneurial and Organizational Diversity, European Research Institute on Cooperative and Social Enterprises, vol. 3(1), pages 35-55, June.
    5. repec:nea:journl:y:2017i:36:p:49-80 is not listed on IDEAS
    6. Carlos Pestana Barros & Emanuel Reis Leão & Nkanga Pedro João Macanda & Zorro Mendes, 2016. "A Bayesian Efficiency Analysis of Angolan Banks," South African Journal of Economics, Economic Society of South Africa, vol. 84(3), pages 484-498, September.
    7. Williams, Gwion & Alsakka, Rasha & ap Gwilym, Owain, 2013. "The impact of sovereign rating actions on bank ratings in emerging markets," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 563-577.
    8. 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.
    9. Williams, Gwion & Alsakka, Rasha & ap Gwilym, Owain, 2015. "Does sovereign creditworthiness affect bank valuations in emerging markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 36(C), pages 113-129.
    10. repec:eee:ecmode:v:67:y:2017:i:c:p:34-44 is not listed on IDEAS
    11. Alsakka, Rasha & ap Gwilym, Owain & Vu, Tuyet Nhung, 2014. "The sovereign-bank rating channel and rating agencies' downgrades during the European debt crisis," Journal of International Money and Finance, Elsevier, vol. 49(PB), pages 235-257.

    More about this item

    Keywords

    International banks; Ratings; Ordered logit models; Country index;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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