Analysts’ Beauty and Performance
Ying Cao (),
Feng Guan (),
Zengquan Li () and
Yong George Yang ()
Additional contact information
Ying Cao: School of Accountancy, Chinese University of Hong Kong, Hong Kong, China
Feng Guan: School of Accountancy, Shanghai University of Finance and Economics, 200433 Shanghai, China
Zengquan Li: School of Accountancy, Shanghai University of Finance and Economics, 200433 Shanghai, China
Yong George Yang: School of Accountancy, Chinese University of Hong Kong, Hong Kong, Chin
Management Science, 2020, vol. 66, issue 9, 4315-4335
Abstract:
We study whether sell-side financial analysts’ physical attractiveness is associated with their job performance. We find that attractive analysts make more accurate earnings forecasts than less attractive analysts. Moreover, more attractive analysts make stock recommendations that are more informative in the short run and more profitable in the long run. Additional analyses reveal that attractive analysts attain their better job performance at least partly through their privileged access to information from firm management. For the sources of the beauty effect, we find that more attractive analysts gain more media exposure, have better connections to institutional investors, and receive more internal support from their employers. Additional evidence suggests that analysts’ physical appearance per se at least partly explains our findings. Overall, our study shows that physical attractiveness has a profound impact on the job performance and information access of sell-side financial analysts.
Keywords: analyst information acquisition; analyst forecast; beauty premium (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)
Downloads: (external link)
https://doi.org/10.287/mnsc.2019.3336 (application/pdf)
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:inm:ormnsc:v:66:y:2020:i:9:p:4315-4335
Access Statistics for this article
More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().