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Policy uncertainty and stock market volatility revisited: The predictive role of signal quality

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  • Afees A. Salisu
  • Riza Demirer
  • Rangan Gupta

Abstract

This paper provides novel insight into the growing literature on the policy uncertainty‐stock market volatility nexus by examining the out‐of‐sample predictive ability of the quality of political signals over stock market volatility at various forecast horizons. Specifically, we examine whether or not accounting for the signal quality in forecasting models within a mixed frequency framework can improve forecast performance and help achieve economic gains for investors. Both in‐ and out‐of‐sample tests, based on a GARCH‐MIDAS framework, show that the quality of the policy signal matters regarding the predictive role of policy uncertainty over subsequent stock market volatility. While high economic policy uncertainty (EPU) predicts high volatility, particularly when the signal quality is high, the positive relationship between EPU and volatility breaks down when the signal quality is low. The improved out‐of‐sample volatility forecasts obtained from the models that account for the quality of policy signals also help typical mean–variance investors achieve improved economic outcomes captured by higher certainty equivalent returns and Sharpe ratios. Although our results indicate clear distinctions between the US and UK stock markets in terms of how market participants process policy signals, they highlight the role of the quality of policy signals as a driver of volatility forecasts with significant economic implications.

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  • Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023. "Policy uncertainty and stock market volatility revisited: The predictive role of signal quality," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2307-2321, December.
  • Handle: RePEc:wly:jforec:v:42:y:2023:i:8:p:2307-2321
    DOI: 10.1002/for.3016
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    1. Das, Sonali & Demirer, Riza & Gupta, Rangan & Mangisa, Siphumlile, 2019. "The effect of global crises on stock market correlations: Evidence from scalar regressions via functional data analysis," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 132-147.
    2. Evan W. Anderson & Eric Ghysels & Jennifer L. Juergens, 2005. "Do Heterogeneous Beliefs Matter for Asset Pricing?," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 875-924.
    3. Baker, Scott R. & Bloom, Nicholas & Davis, Steven J. & Sammo, Marco C., 2021. "What triggers stock market jumps?," LSE Research Online Documents on Economics 113913, London School of Economics and Political Science, LSE Library.
    4. Karl B. Diether & Christopher J. Malloy & Anna Scherbina, 2002. "Differences of Opinion and the Cross Section of Stock Returns," Journal of Finance, American Finance Association, vol. 57(5), pages 2113-2141, October.
    5. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.
    6. Bryan Kelly & Ľuboš Pástor & Pietro Veronesi, 2016. "The Price of Political Uncertainty: Theory and Evidence from the Option Market," Journal of Finance, American Finance Association, vol. 71(5), pages 2417-2480, October.
    7. Lubos Pástor & Pietro Veronesi, 2012. "Uncertainty about Government Policy and Stock Prices," Journal of Finance, American Finance Association, vol. 67(4), pages 1219-1264, August.
    8. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    9. Berkman, Henk & Dimitrov, Valentin & Jain, Prem C. & Koch, Paul D. & Tice, Sheri, 2009. "Sell on the news: Differences of opinion, short-sales constraints, and returns around earnings announcements," Journal of Financial Economics, Elsevier, vol. 92(3), pages 376-399, June.
    10. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    11. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2002. "Breadth of ownership and stock returns," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 171-205.
    12. Pástor, Ľuboš & Veronesi, Pietro, 2013. "Political uncertainty and risk premia," Journal of Financial Economics, Elsevier, vol. 110(3), pages 520-545.
    13. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    14. Xiao-lin Li & Mehmet Balcilar & Rangan Gupta & Tsangyao Chang, 2016. "The Causal Relationship Between Economic Policy Uncertainty and Stock Returns in China and India: Evidence from a Bootstrap Rolling Window Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(3), pages 674-689, March.
    15. Badshah, Ihsan & Demirer, Riza & Suleman, Muhammad Tahir, 2019. "The effect of economic policy uncertainty on stock-commodity correlations and its implications on optimal hedging," Energy Economics, Elsevier, vol. 84(C).
    16. Francisco J. Gomes & Laurence J. Kotlikoff & Luis M. Viceira, 2012. "The Excess Burden of Government Indecision," Tax Policy and the Economy, University of Chicago Press, vol. 26(1), pages 125-164.
    17. Goetzmann, William N. & Massa, Massimo, 2005. "Dispersion of opinion and stock returns," Journal of Financial Markets, Elsevier, vol. 8(3), pages 324-349, August.
    18. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    19. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    20. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(1), pages 85-106.
    21. Bali, Turan G. & Brown, Stephen J. & Tang, Yi, 2017. "Is economic uncertainty priced in the cross-section of stock returns?," Journal of Financial Economics, Elsevier, vol. 126(3), pages 471-489.
    22. Imen Dakhlaoui & Chaker Aloui, 2016. "The Interactive Relationship Between the US Economic Policy Uncertainty and BRIC Stock Markets," International Economics, CEPII research center, issue 146, pages 141-157.
    23. David B. Brown & James E. Smith, 2011. "Dynamic Portfolio Optimization with Transaction Costs: Heuristics and Dual Bounds," Management Science, INFORMS, vol. 57(10), pages 1752-1770, October.
    24. Jonathan Brogaard & Andrew Detzel, 2015. "The Asset-Pricing Implications of Government Economic Policy Uncertainty," Management Science, INFORMS, vol. 61(1), pages 3-18, January.
    25. Goodell, John W. & McGee, Richard J. & McGroarty, Frank, 2020. "Election uncertainty, economic policy uncertainty and financial market uncertainty: A prediction market analysis," Journal of Banking & Finance, Elsevier, vol. 110(C).
    26. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    27. Ajinkya, Bipin B & Gift, Michael J, 1985. "Dispersion of Financial Analysts' Earnings Forecasts and the (Option Model) Implied Standard Deviaitons of Stock Returns," Journal of Finance, American Finance Association, vol. 40(5), pages 1353-1365, December.
    28. Białkowski, Jędrzej & Dang, Huong Dieu & Wei, Xiaopeng, 2022. "High policy uncertainty and low implied market volatility: An academic puzzle?," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1185-1208.
    29. Jiang, Hao & Sun, Zheng, 2014. "Dispersion in beliefs among active mutual funds and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 114(2), pages 341-365.
    30. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    31. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, vol. 164(1), pages 45-59, September.
    32. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    33. Liu, Zhicao & Ye, Yong & Ma, Feng & Liu, Jing, 2017. "Can economic policy uncertainty help to forecast the volatility: A multifractal perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 181-188.
    34. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    35. Snehal Banerjee, 2011. "Learning from Prices and the Dispersion in Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 24(9), pages 3025-3068.
    36. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    37. Liu, Li & Zhang, Tao, 2015. "Economic policy uncertainty and stock market volatility," Finance Research Letters, Elsevier, vol. 15(C), pages 99-105.
    38. Mehmet Balcilar & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2018. "Differences of opinion and stock market volatility: evidence from a nonparametric causality-in-quantiles approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 339-351, April.
    39. Daniel Borup & Johan S. Jakobsen, 2019. "Capturing volatility persistence: a dynamically complete realized EGARCH-MIDAS model," Quantitative Finance, Taylor & Francis Journals, vol. 19(11), pages 1839-1855, November.
    40. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
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    1. Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2023. "Forecasting CPI inflation under economic policy and geo-political uncertainties," Papers 2401.00249, arXiv.org.

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    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
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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