Extrapolative beliefs in the cross-section: What can we learn from the crowds?

• 成果类型: Article
• 署名作者: Da, Zhi; Huang, Xing; Jin, Lawrence J.
• 署名单位: University of Notre Dame; Washington University (WUSTL); California Institute of Technology
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2020.10.003
• 发表日期: 2021
• 页码: 175-196
• 关键词: Return extrapolation; Beliefs in the cross-section; Expectation formation

摘要

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. (C) 2020 Elsevier B.V. All rights reserved.