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Forecasting High-Risk Composite CAMELS Ratings

Author

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  • Lewis Gaul
  • Jonathan Jones
  • Pinar Uysal

Abstract

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Suggested Citation

  • Lewis Gaul & Jonathan Jones & Pinar Uysal, 2019. "Forecasting High-Risk Composite CAMELS Ratings," International Finance Discussion Papers 1252, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgif:1252
    DOI: 10.17016/IFDP.2019.1252
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    References listed on IDEAS

    as
    1. Bassett, William F. & Lee, Seung Jung & Spiller, Thomas Popeck, 2015. "Estimating changes in supervisory standards and their economic effects," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 21-43.
    2. Kamstra, Mark & Kennedy, Peter, 1998. "Combining qualitative forecasts using logit," International Journal of Forecasting, Elsevier, vol. 14(1), pages 83-93, March.
    3. Beverly Hirtle & Jose A. Lopez, 1999. "Supervisory information and the frequency of bank examinations," Economic Policy Review, Federal Reserve Bank of New York, vol. 5(Apr), pages 1-20.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Carlos González-Rossano & Antonia Terán-Bustamante & Marisol Velázquez-Salazar & Antonieta Martínez-Velasco, 2023. "What Drives Profit Income in Mexico’s Main Banks? Evidence Using Machine Learning," Sustainability, MDPI, vol. 15(7), pages 1-19, March.

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    More about this item

    Keywords

    Bank supervision and regulation; early warning models; CAMELS ratings; machine learning;
    All these keywords.

    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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