Should stock returns predictability be ‘hooked on’ long‐horizon regressions?

Theologos Dergiades and Panos K. Pouliasis

International Journal of Finance & Economics, 2023, vol. 28, issue 1, 718-732

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, the stock returns are predictable for wavelengths higher than 5 years. This finding is robust and independent of time, window size and predictor.

Date: 2023
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https://doi.org/10.1002/ijfe.2446

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Working Paper: Should Stock Returns Predictability be hooked on Long Horizon Regressions? (2021)
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