Should stock returns predictability be ‘hooked on’ long‐horizon regressions?
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 r...
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Veröffentlicht in: | International journal of finance and economics 2023-01, Vol.28 (1), p.718-732 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | 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. |
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ISSN: | 1076-9307 1099-1158 |
DOI: | 10.1002/ijfe.2446 |