Anomalies and the Expected Market Return

67 Pages Posted: 7 Apr 2020

See all articles by Xi Dong

Xi Dong

Baruch College / City University of New York

Yan Li

Baruch College, CUNY

David Rapach

Saint Louis University; Washington University in St. Louis

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School; China Academy of Financial Research (CAFR)

Date Written: March 21, 2020

Abstract

We provide the first systematic evidence on the link between long-short anomaly portfolio returns—a cornerstone of the cross-sectional literature—and the time-series predictability of the aggregate market excess return. Using 100 representative anomalies from the literature, we employ a variety of shrinkage techniques (including machine learning, forecast combination, and dimension reduction) to efficiently extract predictive signals in a high-dimensional setting. We find that long-short anomaly portfolio returns evince statistically and economically significant out-of-sample predictive ability for the market excess return. Economically, the predictive ability of anomaly portfolio returns appears to stem from asymmetric limits of arbitrage and overpricing dominance.

Keywords: Out-of-sample predictability, market excess return, long-short anomaly portfolio return, machine learning, asymmetric limits of arbitrage, overpricing dominance

JEL Classification: G11, G14

Suggested Citation

Dong, Xi and Li, Yan and Rapach, David and Zhou, Guofu, Anomalies and the Expected Market Return (March 21, 2020). Baruch College Zicklin School of Business Research Paper No. 2020-02-02, Available at SSRN: https://ssrn.com/abstract=3562774 or http://dx.doi.org/10.2139/ssrn.3562774

Xi Dong

Baruch College / City University of New York ( email )

One Bernard Baruch Way, Box B10-225
New York City, NY 10010
United States

HOME PAGE: http://faculty.baruch.cuny.edu/xdong1/

Yan Li

Baruch College, CUNY ( email )

17 Lexington Avenue
New York, NY 10021
United States

David Rapach (Contact Author)

Saint Louis University ( email )

3674 Lindell Blvd
St. Louis, MO 63108-3397
United States

HOME PAGE: http://https://sites.google.com/slu.edu/daverapach

Washington University in St. Louis

One Brookings Drive
Campus Box 1133
St. Louis, MO 63130-4899
United States

HOME PAGE: http://https://sites.google.com/slu.edu/daverapach

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School ( email )

Washington University
Campus Box 1133
St. Louis, MO 63130-4899
United States
314-935-6384 (Phone)
314-658-6359 (Fax)

HOME PAGE: http://apps.olin.wustl.edu/faculty/zhou/

China Academy of Financial Research (CAFR)

Shanghai Advanced Institute of Finance
Shanghai P.R.China, 200030
China

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
261
Abstract Views
971
rank
128,522
PlumX Metrics