The History of the Cross Section of Stock Returns
Using data spanning the 20th century, we show that most accounting-based return anomalies are spurious. When examined out-of-sample by moving either backward or forward in time, anomalies' average returns decrease, and volatilities and correlations with other anomalies increase. The data-snooping problem is so severe that even the true asset pricing model is expected to be rejected when tested using in-sample data. Our results suggest that asset pricing models should be tested using out-of-sample data or, when not feasible, by whether a model is able to explain half of the in-sample alpha.
We thank Mike Cooper (discussant), Ken French, Travis Johnson (discussant), Mark Leary, Jon Lewellen, David McLean, and Jeff Pontiff for helpful discussions, and seminar and conference participants at University of Lugano, University of Copenhagen, University of Texas at Austin, SFS 2016 Finance Cavalcade, and Western Finance Association 2016 meetings for valuable comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Juhani T Linnainmaa & Michael R Roberts, 2018. "The History of the Cross-Section of Stock Returns," The Review of Financial Studies, vol 31(7), pages 2606-2649.