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Economic Policy Uncertainty and Bank-Level Stock Returns Volatility of the United States: A Mixed-Frequency Perspective

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometrics & Applied Research, Ibadan, Nigeria; Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Ahamuefula E. Ogbonna

    (Centre for Econometrics & Applied Research, Ibadan, Nigeria.)

  • Elie Bouri

    (School of Business, Lebanese American University, Lebanon.)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

Abstract

Using generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) model with monthly Economic Policy Uncertainty (EPU) index and daily stock volatility of 149 banks in the United States from August 2000 to August 2023, we show that EPU plays a significant role in predicting bank stock volatility. Across the groups of large, mid, and small cap banks, stock volatility tends to increase in response to EPU, suggesting that growing uncertainty induces higher volatility in bank stocks. EPU has a stronger impact on large-cap banks. The outperformance of the GARCH-MIDAS-EPU model holds in an out-of-sample analysis, regardless of market capitalization and forecast horizons.

Suggested Citation

  • Afees A. Salisu & Ahamuefula E. Ogbonna & Elie Bouri & Rangan Gupta, 2024. "Economic Policy Uncertainty and Bank-Level Stock Returns Volatility of the United States: A Mixed-Frequency Perspective," Working Papers 202444, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202444
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    References listed on IDEAS

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    More about this item

    Keywords

    Economic policy uncertainty (EPU); Bank-level stock returns volatility; GARCH-MIDAS model;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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