Expert Network Calls

Fisher College of Business Working Paper No. 2022-03-013

Charles A Dice Center Working Paper No. 2022-13

66 Pages Posted: 28 Nov 2022 Last revised: 25 Mar 2025

See all articles by Sean Cao

Sean Cao

University of Maryland - Robert H. Smith School of Business

T. Clifton Green

Emory University - Department of Finance

Lijun (Gillian) Lei

University of North Carolina at Greensboro

Shaojun Zhang

The Ohio State University

Date Written: May 15, 2023

Abstract

Expert networks offer investors in-depth discussions with subject matter experts. Call volume is higher for hard-to-value firms, such as young, technology-oriented, and high intangible asset firms. Calls emphasize non-financial news, with topic distribution predicting future related news coverage in the following months. We find that expert call tone predicts abnormal future stock returns, stock sentiment, and earnings surprises, especially for negative calls and when tone diverges from prevailing market sentiment. Expert call activity also predicts informed trading and improved price efficiency. Our findings highlight expert networks as a valuable alternative information source, helping investors identify and interpret value-related firm information.

Keywords: JEL: G11, G12, G14 Expert Networks, Price Efficiency, Hedge Funds

JEL Classification: G11, G12, G14

Suggested Citation

Cao, Sean S. and Green, T. Clifton and Lei, Lijun and Zhang, Shaojun, Expert Network Calls (May 15, 2023). Fisher College of Business Working Paper No. 2022-03-013, Charles A Dice Center Working Paper No. 2022-13, Available at SSRN: https://ssrn.com/abstract=4280865 or http://dx.doi.org/10.2139/ssrn.4280865

Sean S. Cao

University of Maryland - Robert H. Smith School of Business ( email )

College Park, MD 20742-1815
United States

T. Clifton Green (Contact Author)

Emory University - Department of Finance ( email )

1300 Clifton Rd.
Atlanta, GA 30322-2710
United States
404-727-5167 (Phone)
404-727-5238 (Fax)

Lijun Lei

University of North Carolina at Greensboro ( email )

P.O.Box 26170
Greensboro, NC 27412
United States

Shaojun Zhang

The Ohio State University

2100 Neil Avenue
Columbus, OH 43210-1144
United States

HOME PAGE: http://sites.google.com/view/zhangshaojun

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