Retail Investor Attention and Insider Trading

63 Pages Posted: 22 Apr 2021 Last revised: 22 Aug 2022

See all articles by Sattar Mansi

Sattar Mansi

Virginia Tech

Lin Peng

City University of New York, Baruch College - Zicklin School of Business - Department of Economics and Finance

Jianping Qi

University of South Florida - College of Business Administration

Han Shi

Louisiana State University, Shreveport

Date Written: August 8, 2022

Abstract

We identify a new mechanism of opportunistic insider trading that is associated with attention-driven mispricing. Insiders are more likely to sell their company’s stock after increases in retail attention, and they are more likely to buy after attention decreases. A long-short insider-trading portfolio conditioned on attention generates 65.8% higher abnormal returns than that of an unconditional portfolio. The results are stronger for lottery stocks and for firms with higher retail ownership or weaker governance. The attention-based trading is unrelated to firm fundamentals, is less likely to trigger SEC enforcement actions, and becomes more prevalent following waves of SEC enforcement.

Keywords: Insider Trading; Retail Attention; Governance; SEC Enforcement

JEL Classification: G02, G12, G14

Suggested Citation

Mansi, Sattar and Peng, Lin and Qi, Jianping and Shi, Han, Retail Investor Attention and Insider Trading (August 8, 2022). Available at SSRN: https://ssrn.com/abstract=3831504 or http://dx.doi.org/10.2139/ssrn.3831504

Sattar Mansi

Virginia Tech ( email )

Lin Peng (Contact Author)

City University of New York, Baruch College - Zicklin School of Business - Department of Economics and Finance ( email )

17 Lexington Avenue
New York, NY 10010
United States

Jianping Qi

University of South Florida - College of Business Administration ( email )

USF College of Business
4202 E. Fowler Avenue, BSN 3403
Tampa, FL 33620-5500
United States
813-974-9856 (Phone)
813-974-3084 (Fax)

Han Shi

Louisiana State University, Shreveport ( email )

Shreveport, LA
United States

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