City Research Online

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 longhorizons. 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.

Publication Type:	Article
Additional Information:	This is the peer reviewed version of the following article: Dergiades, T. and Pouliasis, P. K. (2020). Should Stock Returns Predictability be “hooked on” Long Horizon Regressions?. International Journal of Finance and Economics, which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School > Finance
SWORD Depositor:	Symplectic Administrator

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