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Incorporating Economic Policy Uncertainty in US Equity Premium Models: A Nonlinear Predictability Analysis

Author

Listed:
  • Stelios Bekiros

    () (European University Institute (EUI) and IPAG Business School)

  • Rangan Gupta

    () (Department of Economics, University of Pretoria and IPAG Business School)

  • Anandamayee Majumdar

    () (Center for Advanced Statistics and Econometrics, Soochow University, Suzhou, China)

Abstract

Information on economic policy uncertainty does matter in predicting the US equity premium, especially when accounting for structural instabilities and omitted nonlinearities in their relationship, via a quantile predictive regression approach over the monthly period 1900:1-2014:2. Unlike as suggested by a linear mean-based predictive model, the extended quantile regression model with the incorporation of the EPU proxy, enhances significantly the out-of-sample stock return predictability. This is observed especially when the market is neutral, exhibits a side or mildly upward trending behavior, yet not when the market appears to turn highly bullish.

Suggested Citation

  • Stelios Bekiros & Rangan Gupta & Anandamayee Majumdar, 2015. "Incorporating Economic Policy Uncertainty in US Equity Premium Models: A Nonlinear Predictability Analysis," Working Papers 201545, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201545
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    References listed on IDEAS

    as
    1. Jones, Paul M. & Olson, Eric, 2013. "The time-varying correlation between uncertainty, output, and inflation: Evidence from a DCC-GARCH model," Economics Letters, Elsevier, vol. 118(1), pages 33-37.
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    5. Bekiros, Stelios & Gupta, Rangan & Kyei, Clement, 2016. "On economic uncertainty, stock market predictability and nonlinear spillover effects," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 184-191.
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    Cited by:

    1. 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.
    2. repec:eee:ecmode:v:64:y:2017:i:c:p:74-81 is not listed on IDEAS
    3. repec:eee:ecosys:v:42:y:2018:i:2:p:295-306 is not listed on IDEAS
    4. repec:eee:intfin:v:55:y:2018:i:c:p:134-150 is not listed on IDEAS
    5. Suleman, Tahir & Gupta, Rangan & Balcilar, Mehmet, 2017. "Does country risks predict stock returns and volatility? Evidence from a nonparametric approach," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1173-1195.
    6. repec:eee:finlet:v:21:y:2017:i:c:p:214-221 is not listed on IDEAS
    7. Balcilar, Mehmet & Bonato, Matteo & Demirer, Riza & Gupta, Rangan, 2018. "Geopolitical risks and stock market dynamics of the BRICS," Economic Systems, Elsevier, vol. 42(2), pages 295-306.
    8. Gupta, Rangan & Mwamba, John W. Muteba & Wohar, Mark E., 2018. "The role of partisan conflict in forecasting the U.S. equity premium: A nonparametric approach," Finance Research Letters, Elsevier, vol. 25(C), pages 131-136.
    9. Rangan Gupta & Marian Risse & David A. Volkman & Mark E. Wohar, 2017. "The Role of Term Spread and Pattern Changes in Predicting Stock Returns and Volatility of the United Kingdom: Evidence from a Nonparametric Causality-in-Quantiles Test Using Over 250 Years of Data," Working Papers 201755, University of Pretoria, Department of Economics.
    10. repec:ebl:ecbull:eb-17-00090 is not listed on IDEAS
    11. Mehmet Balcilar & Esin Cakan & Rangan Gupta, 2016. "Does U.S. News Impact Asian Emerging Markets? Evidence from Nonparametric Causality-in-Quantiles Test," Working Papers 201631, University of Pretoria, Department of Economics.
    12. repec:eee:finlet:v:22:y:2017:i:c:p:249-258 is not listed on IDEAS
    13. repec:eee:phsmap:v:498:y:2018:i:c:p:123-136 is not listed on IDEAS
    14. Mehmet Balcilar & Deven Bathia & Riza Demirer & Rangan Gupta, 2017. "Credit Ratings and Predictability of Stock Returns and Volatility of the BRICS and the PIIGS: Evidence from a Nonparametric Causality-in-Quantiles Approach," Working Papers 201719, University of Pretoria, Department of Economics.

    More about this item

    Keywords

    stock markets; economic uncertainty; predictability; quantile regression;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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