Extrapolative Beliefs in the Cross-Section: What Can We Learn from the Crowds?

58 Pages Posted: 22 Mar 2018 Last revised: 8 Sep 2020

See all articles by Zhi Da

Zhi Da

University of Notre Dame - Mendoza College of Business

Xing Huang

Washington University in St. Louis - Olin Business School

Lawrence J. Jin

California Institute of Technology

Date Written: September 4, 2020

Abstract

Using novel data from a crowdsourcing platform for ranking stocks, we investigate how investors form expectations about stock returns over the next week. We find that investors extrapolate from stocks' recent past returns, with more weight on more recent returns, especially when recent returns are negative, salient, or from a dispersed cross-section. Such extrapolative beliefs are stronger among nonprofessionals and large stocks. Moreover, consensus rankings negatively predict returns over the next week, more so among stocks with low institutional ownership and a high degree of extrapolation. A trading strategy that sorts stocks on investor beliefs generates an economically significant profit.

Keywords: return extrapolation; beliefs in the cross-section; expectation formation

JEL Classification: G02; G11; G12

Suggested Citation

Da, Zhi and Huang, Xing and Jin, Lawrence J., Extrapolative Beliefs in the Cross-Section: What Can We Learn from the Crowds? (September 4, 2020). Journal of Financial Economics (JFE), Forthcoming, Available at SSRN: https://ssrn.com/abstract=3144849 or http://dx.doi.org/10.2139/ssrn.3144849

Zhi Da

University of Notre Dame - Mendoza College of Business ( email )

Notre Dame, IN 46556-5646
United States

Xing Huang

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

Simon Hall 211
Washington University in St. Louis
St. Louis, MO 63130
United States

Lawrence J. Jin (Contact Author)

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

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