Publication Type
Working Paper
Version
publishedVersion
Publication Date
1-2020
Abstract
This study shows that analyst research benefits from the sharing of information about economically connected industries among colleagues. Measuring the intensity of potential information sharing with the level of economic connection between an analyst’s industry and her colleagues’ industries, we find that it is positively correlated with an analyst’s earnings forecast accuracy, stock recommendation profitability, coverage breadth, and report frequency after controlling for other determinants including broker or analyst fixed effects. We also find that analysts are more likely to issue reports when highly connected colleagues produce information. We show that sharing information with colleagues covering downstream (upstream) industries benefits an analyst’s revenue (expense) forecasts, and that an analyst’s performance improves (deteriorates) after an economically connected colleague joins (departs) the brokerage firm. Cross-sectionally, information sharing benefits an analyst’s research more when her colleagues have higher research quality, and when she and her colleagues have stronger social ties. Finally, we find that investors recognize the benefits of information sharing: they react more strongly to research reports issued by analysts whose covered industries have a higher level of economic connection to those of colleagues, and are more likely to vote such analysts as All-Stars.
Keywords
financial analyst, information sharing, economically connected industries, forecast accuracy, recommendation profitability, social network, All-Star ranking
Discipline
Accounting | Finance and Financial Management | Management Information Systems
Research Areas
Corporate Reporting and Disclosure
First Page
1
Last Page
64
Identifier
10.2139/ssrn.3502820
Publisher
SSRN
Citation
HUANG, Allen; LIN, An-ping; and ZANG, Amy.
Cross-industry information sharing and analyst performance. (2020). 1-64.
Available at: https://ink.library.smu.edu.sg/soa_research/1839
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.2139/ssrn.3502820
Included in
Accounting Commons, Finance and Financial Management Commons, Management Information Systems Commons
Comments
Published Journal of Accounting and Economics (2022) DOI: https://doi.org/10.1016/j.jacceco.2022.101496