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Interest Rate Uncertainty and the Predictability of Bank Revenues

Author

Listed:
  • Oguzhan Cepni

    (Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050, Ankara, Turkey)

  • Riza Demirer

    (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1102, USA)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Ahmet Sensoy

    (Bilkent University, Faculty of Business Administration, Ankara 06800, Turkey)

Abstract
This paper examines the predictive power of interest rate uncertainty over preprovision net revenues (PPNR) in a large panel of bank holding companies (BHC). Utilizing a linear dynamic panel model, we show that supplementing forecasting models with interest rate uncertainty improves the forecasting performance with the augmented model yielding lower forecast errors in comparison to a baseline model which includes unemployment rate, federal funds rate, and spread variables. Further separating PPNRs into two components that reflect net interest and noninterest income, we show that the predictive power of interest rate uncertainty is concentrated on the non-interest component of bank revenues. Finally, examining the point predictions under a severely stressed scenario, we show that the model can successfully predict the negative effect on overall bank revenues with a rise in the non-interest component of income during 2009:Q1. Overall, the findings suggest that stress testing exercises that involve bank revenue models can benefit from the inclusion of interest rate uncertainty and the cross-sectional information embedded in the panel of BHCs.

Suggested Citation

  • Oguzhan Cepni & Riza Demirer & Rangan Gupta & Ahmet Sensoy, 2020. "Interest Rate Uncertainty and the Predictability of Bank Revenues," Working Papers 202040, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202040
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    References listed on IDEAS

    as
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    2. Xie, Xin & Mirza, Nawazish & Umar, Muhammad & Ji, Xiaoman, 2024. "Covid-19 and market discipline: Evidence from the banking sector in emerging markets," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 612-621.

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    More about this item

    Keywords

    Bank stress tests; Empirical Bayes; Interest rate uncertainty; Out-of-sample forecasts;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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