Can Investors Adjust for Managerial Bias?

James Smith and Lisa Koonce

Journal of Behavioral Finance, 2023, vol. 24, issue 1, 41-55

Abstract: Financial information from firms often contains biased information. In this study, we posit and experimentally test the idea that investors will have difficulty in unraveling known biases in management’s earnings forecasts but will be most likely to fully adjust when the information about bias is in quantitative, EPS form and the investor’s judgment is compatible with that bias information (also in quantitative, EPS form). Results from three experiments suggest that indeed quantification and compatibility are beneficial for unraveling managerial bias, but even under these conditions not all investors are able to unravel. We also show that this result is robust to several moderator variables that capture factors that are commonly found in the management earnings forecast setting. Our study has implications for firm managers, regulators, and investors.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/15427560.2021.1913161 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:hbhfxx:v:24:y:2023:i:1:p:41-55

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/hbhf20

DOI: 10.1080/15427560.2021.1913161

Access Statistics for this article

Journal of Behavioral Finance is currently edited by Brian Bruce

More articles in Journal of Behavioral Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().