Prospect Theory and Stock Market Anomalies

61 Pages Posted: 8 Nov 2019

See all articles by Nicholas Barberis

Nicholas Barberis

Yale School of Management; National Bureau of Economic Research (NBER)

Lawrence J. Jin

California Institute of Technology

Baolian Wang

University of Florida - Department of Finance, Insurance and Real Estate

Date Written: October 29, 2019

Abstract

We present a new model of asset prices in which investors evaluate risk according to prospect theory and examine its ability to explain 22 prominent stock market anomalies. The model incorporates all the elements of prospect theory, takes account of investors' prior gains and losses, and makes quantitative predictions about an asset's average return based on empirical estimates of its beta, volatility, skewness, and capital gain overhang. We find that the model is helpful for thinking about a majority of the anomalies we consider. It performs particularly well for the momentum, volatility, distress, and profitability anomalies, but poorly for the value anomaly. For several anomalies, the model explains not only the average returns of extreme anomaly deciles, but also more granular patterns in the average returns of intermediate deciles.

Keywords: prospect theory, loss aversion, probability weighting, cross-section

JEL Classification: G11, G12

Suggested Citation

Barberis, Nicholas and Jin, Lawrence J. and Wang, Baolian, Prospect Theory and Stock Market Anomalies (October 29, 2019). Available at SSRN: https://ssrn.com/abstract=3477463 or http://dx.doi.org/10.2139/ssrn.3477463

Nicholas Barberis (Contact Author)

Yale School of Management ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States
203-436-0777 (Phone)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Lawrence J. Jin

California Institute of Technology ( email )

1200 E. California Blvd.
MC 228-77
Pasadena, CA 91125
United States
626-395-4558 (Phone)

HOME PAGE: http://www.hss.caltech.edu/content/lawrence-jin

Baolian Wang

University of Florida - Department of Finance, Insurance and Real Estate ( email )

314 Stuzin Hall
Gainesville, FL 32611
United States

HOME PAGE: http://www.wangbaolian.com

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