Persistent Predictors and the Cross-Section of Stock Returns

70 Pages Posted: 5 Sep 2019 Last revised: 4 May 2020

See all articles by Devraj Basu

Devraj Basu

SKEMA Business School - Lille Campus

Marta Szymanowska

Erasmus University Rotterdam (EUR) - Department of Finance; Erasmus Research Institute of Management (ERIM)

Date Written: May 3, 2020

Abstract

We show that when returns are predictable, persistent predictors, known to bias time-series predictive regressions, also bias the estimation of the cross-sectional moments of asset return distribution, especially the variance-covariance matrix of returns. Our findings, further, suggest that the underlying persistence levels together with sample size influence the conclusions of asset pricing tests. We define a test statistic that is immune to this bias and shows consistent results across the persistence levels and sample sizes.

Keywords: asset pricing, persistent predictors, stochastic discount factor bounds, conditioning information

JEL Classification: G11, G12

Suggested Citation

Basu, Devraj and Szymanowska, Marta, Persistent Predictors and the Cross-Section of Stock Returns (May 3, 2020). Available at SSRN: https://ssrn.com/abstract=3444841 or http://dx.doi.org/10.2139/ssrn.3444841

Devraj Basu

SKEMA Business School - Lille Campus ( email )

Avenue Willy Brandt, Euralille
Lille, 59777
France

Marta Szymanowska (Contact Author)

Erasmus University Rotterdam (EUR) - Department of Finance ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands
+31104089607 (Phone)

HOME PAGE: http://www.rsm.nl/mszymanowska

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

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