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A macroprudential look into the risk-return framework of banks’ profitability

Author

Listed:
  • Joana Passinhas
  • Ana Pereira

Abstract

Ensuring the resilience of the financial system implies managing a trade-off between expected bank profitability and tail risk in bank returns. To describe this trade-off, we estimate a dynamic quantile regression model using bank-level data for Portugal that links future bank profitability to the current cyclical systemic risk environment net of the prevailing level of capital-based resilience (residual cyclical systemic risk). We find that an increase in residual cyclical systemic risk negatively affects the conditional distribution of bank profitability at the medium-term projection horizons, confirming the findings in the literature. We propose a novel calibration rule for the countercyclical capital buffer (CCyB), which is flexible enough to accommodate different preferences of the policymaker and factors in the prevailing levels of cyclical systemic risk and capital-based resilience. We illustrate the operationalisation of this rule under different assumptions for the policymaker preferences and show how tightening capital requirements alters the risk-return relationship of future profitability in the banking sector. We find evidence that increasing the CCyB rate improves the outlook for medium-term downside risk in bank profitability and worsens the outlook for short-term expected profitability, stressing the tradeoff faced by the policymaker when deploying policy instruments and the misalignment in the horizons at which costs and benefits take place.

Suggested Citation

  • Joana Passinhas & Ana Pereira, 2023. "A macroprudential look into the risk-return framework of banks’ profitability," Working Papers w202303, Banco de Portugal, Economics and Research Department.
  • Handle: RePEc:ptu:wpaper:w202303
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    References listed on IDEAS

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    1. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.
    2. Virginie Coudert & Julien Idier, 2018. "Reducing model risk in early warning systems for banking crises in the euro area," International Economics, CEPII research center, issue 156, pages 98-116.
    3. Cyril Couaillier & Valerio Scalone, 2021. "Risk-to-Buffer: Setting Cyclical and Structural Capital Buffers through Banks Stress Tests," Working papers 830, Banque de France.
    4. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
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    Cited by:

    1. De Nora, Giorgia & Pereira, Ana & Pirovano, Mara & Stammwitz, Florian, 2025. "From losses to buffer - calibrating the positive neutral CCyB rate in the euro area," Working Paper Series 3061, European Central Bank.
    2. Herrera, Luis & Pirovano, Mara & Scalone, Valerio, 2025. "From risk to buffer: calibrating the positive neutral CCyB rate in the euro area," Working Paper Series 3075, European Central Bank.

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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • 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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