On the Economic Value of Stock Market Return Predictors

54 Pages Posted: 10 May 2019

See all articles by Scott Cederburg

Scott Cederburg

University of Arizona - Department of Finance

Travis L. Johnson

The University of Texas at Austin

Michael S. O'Doherty

University of Missouri at Columbia - Department of Finance

Date Written: November 17, 2018

Abstract

Kandel and Stambaugh (1996) demonstrate that forecasting variables with weak statistical support in predictive return regressions can exert considerable economic influence on portfolio decisions. Using a Bayesian vector autoregression framework with stochastic volatility in market returns and predictor variables, we assess the economic value of return predictability and reach a complementary conclusion. Statistically strong predictors can be economically unimportant if they tend to take extreme values in high-volatility periods, have low persistence, and/or follow distributions with fat tails. Several popular predictors exhibit these properties such that their impressive statistical results do not translate into large economic gains for investors.

Keywords: Market return predictability, Bayesian investors, Stochastic volatility, Multiperiod horizons

JEL Classification: G10, G11, G12

Suggested Citation

Cederburg, Scott and Johnson, Travis L. and O'Doherty, Michael S., On the Economic Value of Stock Market Return Predictors (November 17, 2018). Available at SSRN: https://ssrn.com/abstract=3372629 or http://dx.doi.org/10.2139/ssrn.3372629

Scott Cederburg (Contact Author)

University of Arizona - Department of Finance ( email )

McClelland Hall
P.O. Box 210108
Tucson, AZ 85721-0108
United States

Travis L. Johnson

The University of Texas at Austin ( email )

2110 Speedway Stop B6600
Austin, TX Texas 78712
United States
6178995325 (Phone)

HOME PAGE: http://travislakejohnson.com

Michael S. O'Doherty

University of Missouri at Columbia - Department of Finance ( email )

Robert J. Trulaske, Sr. College of Business
403 Cornell Hall
Columbia, MO 65211
United States

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