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On Economic Uncertainty, Stock Market Predictability and Nonlinear Spillover Effects

Author

Listed:
  • Stelios Bekiros

    (IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Clement Kyei

    (Department of Economics, University of Pretoria)

Abstract
This paper uses a k-th order nonparametric Granger causality test to analyze whether firm-level, economic policy and macroeconomic uncertainty indicators predict movements in real stock returns and their volatility. Linear Granger causality tests show that whilst economic policy and macroeconomic uncertainty indices can predict stock returns, firm-level uncertainty measures possess no predictability. However, given the existence of structural breaks and inherent nonlinearities in the series, we employ a nonparametric causality methodology, since the linear model is misspecified and the results emanating from it cannot be considered reliable. The nonparametric test reveals that, in fact, there is in general no predictability from the various measures of uncertainties, i.e., firm-level, macroeconomic, and economic policy uncertainty, for real stock returns. In turn, the predictability is concentrated in the volatility of real stock returns, except under the case of firm-level uncertainty. Thus, our results not only emphasize the role of economic and firm-level uncertainty measures in predicting volatility of stock returns, but also presage against using linear models which are likely to suffer from misspecification in the presence of parameter instability and nonlinear spillover effects.

Suggested Citation

  • Stelios Bekiros & Rangan Gupta & Clement Kyei, 2015. "On Economic Uncertainty, Stock Market Predictability and Nonlinear Spillover Effects," Working Papers 201508, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201508
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    References listed on IDEAS

    as
    1. Chang, Tsangyao & Chen, Wen-Yi & Gupta, Rangan & Nguyen, Duc Khuong, 2015. "Are stock prices related to the political uncertainty index in OECD countries? Evidence from the bootstrap panel causality test," Economic Systems, Elsevier, vol. 39(2), pages 288-300.
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    5. Kang, Wensheng & Ratti, Ronald A., 2013. "Oil shocks, policy uncertainty and stock market return," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 305-318.
    6. 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.
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    12. Nishiyama, Yoshihiko & Hitomi, Kohtaro & Kawasaki, Yoshinori & Jeong, Kiho, 2011. "A consistent nonparametric test for nonlinear causality—Specification in time series regression," Journal of Econometrics, Elsevier, vol. 165(1), pages 112-127.
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    More about this item

    Keywords

    Economic policy; stock markets; nonlinear causality;
    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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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