Should Stock Returns Predictability be hooked on Long Horizon Regressions?

Theologos Dergiades and Panos K. Pouliasis
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Panos K. Pouliasis: Cass Business School

Discussion Paper Series from Department of Economics, University of Macedonia

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.

Keywords: Stock Returns; Long-Horizon Predictability, Frequency Domain. (search for similar items in EconPapers)
JEL-codes: C10 G17 G32 (search for similar items in EconPapers)
Date: 2021-02, Revised 2021-02
New Economics Papers: this item is included in nep-cfn, nep-cwa, nep-fmk and nep-ore
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Journal Article: Should stock returns predictability be ‘hooked on’ long‐horizon regressions? (2023)
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