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Should Stock Returns Predictability be hooked on Long Horizon Regressions?

Author

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  • Theologos Dergiades

    (Department of International and European Studies, University of Macedonia)

  • Panos K. Pouliasis

    (Cass Business School)

Abstract

This paper re-examines stock returns predictability over the business cycle using price-dividend and price-earnings valuation ratios as predictors. Unlike prior studies that habitually implement long-horizon/predictive regressions, we conduct a testing framework in the frequency domain. Predictive regressions support no predictability; in contrast, our results in the frequency domain verify significant predictability at medium and long horizons. To robustify predictability patterns, the analysis is executed repetitively for fixed-length rolling samples of various sizes. Overall, stock returns are predictable for wavelengths higher than five years. This finding is robust and independent of time, window size and predictor.

Suggested Citation

  • Theologos Dergiades & Panos K. Pouliasis, 2021. "Should Stock Returns Predictability be hooked on Long Horizon Regressions?," Discussion Paper Series 2021_03, Department of Economics, University of Macedonia, revised Feb 2021.
    • Handle: RePEc:mcd:mcddps:2021_03
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    More about this item

    Keywords

    Stock Returns; Long-Horizon Predictability; Frequency Domain.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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