Overconfident Institutions and Their Self-Attribution Bias: Evidence from Earnings Announcements. (16th August 2021)
- Record Type:
- Journal Article
- Title:
- Overconfident Institutions and Their Self-Attribution Bias: Evidence from Earnings Announcements. (16th August 2021)
- Main Title:
- Overconfident Institutions and Their Self-Attribution Bias: Evidence from Earnings Announcements
- Authors:
- Chou, Hsin-I
Li, Mingyi
Yin, Xiangkang
Zhao, Jing - Abstract:
- Abstract: Institutional demand for a stock before its earnings announcement is negatively related to subsequent returns. The relation is not attributable to the price pressure of institutional demand and is stronger for stocks with higher information asymmetry and/or greater valuation difficulty. These findings support the notion that overconfident institutions misprice stocks. Following announcements, institutions' behavior exhibits the outcome-dependent feature of self-attribution bias. Whether they become more overconfident and delay their mispricing correction depends on whether earnings news confirms their preannouncement trades. This behavioral bias also offers a new explanation for the well-known post-earnings-announcement drift.
- Is Part Of:
- Journal of financial and quantitative analysis. Volume 56:Number 5(2021)
- Journal:
- Journal of financial and quantitative analysis
- Issue:
- Volume 56:Number 5(2021)
- Issue Display:
- Volume 56, Issue 5 (2021)
- Year:
- 2021
- Volume:
- 56
- Issue:
- 5
- Issue Sort Value:
- 2021-0056-0005-0000
- Page Start:
- 1738
- Page End:
- 1770
- Publication Date:
- 2021-08-16
- Subjects:
- Finance -- Periodicals
Investments -- Mathematics -- Periodicals
332.05 - Journal URLs:
- http://catalog.hathitrust.org/api/volumes/oclc/1754589.html ↗
http://depts.washington.edu/jfqa ↗
http://journals.cambridge.org/action/displayJournal?jid=JFQ ↗
http://www.jstor.org/journals/00221090.html ↗ - DOI:
- 10.1017/S002210902000037X ↗
- Languages:
- English
- ISSNs:
- 0022-1090
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 18370.xml