Prospect Theory and Stock Market Anomalies

65 Pages Posted: 18 May 2020

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

Multiple version iconThere are 2 versions of this paper

Date Written: May 2020

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 volatility, skewness, and past capital gain. We find that the model is helpful for thinking about a majority of the 22 anomalies.

Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Suggested Citation

Barberis, Nicholas and Jin, Lawrence J. and Wang, Baolian, Prospect Theory and Stock Market Anomalies (May 2020). NBER Working Paper No. w27155, Available at SSRN: https://ssrn.com/abstract=3603785

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

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
22
Abstract Views
338
PlumX Metrics