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Predicting Firm-Level Volatility in the United States: The Role of Monetary Policy Uncertainty

Author

Listed:
  • Matthew W. Clance

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

  • Riza Demirer

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

  • Rangan Gupta

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

  • Clement Kweku Kyei

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

Abstract

This paper provides novel evidence for the predictive power of monetary policy uncertainty (MPU) over stock return volatility at the firm level based on a dataset constructed from 9,458 U.S. firms. Our findings show that monetary policy uncertainty contains significant predictive information over realized and implied volatilities at both the firm- and industry-level, with higher policy uncertainty predicting higher volatility in subsequent periods. While the strongest possible volatility effect is observed in the case of Retail Trade, we observe opposite results for Mining with high policy uncertainty predicting lower volatility in this sector. We argue that the dual nature of the underlying commodity for Mining companies, both as a consumption and investment asset, drives the negative effect of policy uncertainty on volatility in this sector. Nevertheless, the findings highlight the predictive information captured by monetary policy actions on the idiosyncratic component of equity market volatility.

Suggested Citation

  • Matthew W. Clance & Riza Demirer & Rangan Gupta & Clement Kweku Kyei, 2020. "Predicting Firm-Level Volatility in the United States: The Role of Monetary Policy Uncertainty," Working Papers 202007, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:202007
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    Cited by:

    1. Demirer, Riza & Gupta, Rangan & Salisu, Afees A. & van Eyden, ReneƩ, 2023. "Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 295-302.

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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