The Supraview of Return Predictive Signals

49 Pages Posted: 18 May 2012 Last revised: 17 Jan 2013

See all articles by Jeremiah Green

Jeremiah Green

Pennsylvania State University

John R. M. Hand

University of North Carolina Kenan-Flagler Business School

Frank Zhang

Yale School of Management

Date Written: May 13, 2012


This study speaks to investment academics and practitioners by describing and analyzing the population of return predictive signals (RPS) publicly identified during the period 1970-2010. Our supraview brings to light a number of new facts about the population of RPS, including that more than 330 signals have been discovered and reported; the properties of newly discovered RPS remain stable over time; and RPS with higher mean returns have not only larger standard deviations of returns, but higher Sharpe ratios too. Using a sample of RPS, we estimate the average signed (absolute) cross-correlation of returns in the population of RPS to be just 0.05 (0.25). Abstracting from implementation costs, we show that this low of an average signed cross-correlation in RPS returns means that in theory an optimal portfolio of all RPS can have an equally-weighted (value-weighted) annualized Sharpe ratio as large as 3.0 (4.5). We also show that the probability that a given RPS has a positive alpha after being orthogonalized against five (25) other randomly chosen RPS is 62% (32%). Our study suggests that practitioners can expect to create value for their clients by hunting down new sources of alpha, and that academics testing for the existence of a new RPS do not need to orthogonalize the returns of that RPS against all pre-existing RPS. However, our findings also pose a challenge to academic theorists, since they imply that either U.S. stock markets are pervasively inefficient, or there exist a much larger number of rationally priced sources of risk in equity returns than ever previously thought.

Keywords: Return predictive signals, supraview, efficient markets

JEL Classification: G12, G14

Suggested Citation

Green, Jeremiah and Hand, John R. M. and Zhang, Frank, The Supraview of Return Predictive Signals (May 13, 2012). Review of Accounting Studies, Forthcoming. Available at SSRN: or

Jeremiah Green

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

John R. M. Hand (Contact Author)

University of North Carolina Kenan-Flagler Business School ( email )

McColl Building
Chapel Hill, NC 27599-3490
United States
919-962-3173 (Phone)
919-962-4727 (Fax)

Frank Zhang

Yale School of Management ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States

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