Social Transmission Bias: Evidence from an Online Investor Platform

66 Pages Posted: 27 Apr 2022

See all articles by Pengfei Sui

Pengfei Sui

The Chinese University of Hong Kong, Shenzhen

Baolian Wang

University of Florida - Department of Finance, Insurance and Real Estate

Date Written: April 12, 2022

Abstract

Using data from a Twitter-like investor social platform, we document evidence consistent with the self-enhancing transmission bias. We find that investors are more likely to post about their better-performing stocks. Their followers are more likely to buy the posted stocks than the non-posted stocks and the effect of postings on follow-up purchases is related to postings’ perceived credibility. Both the relationship between performance and postings and the relationship between postings and follow-up purchases vary with stock characteristics in a way that facilitates the spread of high-variance, high-skewness, and extrapolative strategies. We also document that the social network features influential nodes.

Keywords: social network; self-enhancing transmission bias; social trading platform

JEL Classification: D91, G41

Suggested Citation

Sui, Pengfei and Wang, Baolian, Social Transmission Bias: Evidence from an Online Investor Platform (April 12, 2022). Available at SSRN: https://ssrn.com/abstract=4081644 or http://dx.doi.org/10.2139/ssrn.4081644

Pengfei Sui

The Chinese University of Hong Kong, Shenzhen ( email )

2001 Longxiang Road, Longgang District
Shenzhen, 518172
China
15810011687 (Phone)
518172 (Fax)

HOME PAGE: http://www.pengfeisui.com

Baolian Wang (Contact Author)

University of Florida - Department of Finance, Insurance and Real Estate ( email )

314 Stuzin Hall
Gainesville, FL 32611
United States

HOME PAGE: http://www.wangbaolian.com

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