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A Cost-Benefit Analysis of Capital Requirements Adjusted for Model Risk

Author

Listed:
  • Walter Farkas

    (University of Zurich - Department of Banking and Finance; Swiss Finance Institute; ETH Zürich)

  • Fulvia Fringuellotti

    (Federal Reserve Banks - Federal Reserve Bank of New York)

  • Radu Tunaru

    (University of Sussex)

Abstract

Capital adequacy is the key microprudential and macroprudential tool of banking regulation. Financial models of capital adequacy are subject to errors, which may prevent from estimating a sufficient capital base to absorb bank losses during economic downturns. In this paper, we propose a general method to account for model risk in capital requirements calculus related to market risk. We then evaluate and compare our capital requirements values with those obtained under Basel 2.5 and the new Basel 4 regulation. Capital requirements adjusted for model risk perform well in containing losses generates in normal and stressed times. In addition, they are as conservative as Basel 4 capital requirements, but they exhibit less fluctuations over time.

Suggested Citation

  • Walter Farkas & Fulvia Fringuellotti & Radu Tunaru, 2020. "A Cost-Benefit Analysis of Capital Requirements Adjusted for Model Risk," Swiss Finance Institute Research Paper Series 20-86, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp2086
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    Cited by:

    1. Cosma, Simona & Rimo, Giuseppe & Torluccio, Giuseppe, 2023. "Knowledge mapping of model risk in banking," International Review of Financial Analysis, Elsevier, vol. 89(C).
    2. Alessandro Avellone & Ilaria Foroni & Chiara Pederzoli, 2025. "Minimum capital requirement portfolios according to the new Basel framework for market risk," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 39(2), pages 171-192, June.
    3. Josef Sveda, 2025. "Navigating Banking Resilience: Bail-ins & Bailouts in the Czech Banking Sector," Working Papers 2025/5, Czech National Bank, Research and Statistics Department.
    4. repec:hal:wpaper:hal-03675291 is not listed on IDEAS
    5. Cyril Bénézet & Stéphane Crépey, 2024. "Handling model risk with XVAs," Post-Print hal-03675291, HAL.
    6. Li, Dan & Clements, Adam & Drovandi, Christopher, 2023. "A Bayesian approach for more reliable tail risk forecasts," Journal of Financial Stability, Elsevier, vol. 64(C).
    7. Cyril B'en'ezet & St'ephane Cr'epey, 2022. "Handling model risk with XVAs," Papers 2205.11834, arXiv.org, revised Aug 2024.
    8. Andrés Alonso Robisco & José Manuel Carbó Martínez, 2022. "Measuring the model risk-adjusted performance of machine learning algorithms in credit default prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-35, December.

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    Keywords

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    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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