Difficulties in obtaining a representative sample of retail trades from public data sources

59 Pages Posted: 18 Oct 2023 Last revised: 13 May 2024

See all articles by Robert H. Battalio

Robert H. Battalio

University of Notre Dame - Department of Finance

Robert H. Jennings

Indiana University - Kelley School of Business - Department of Finance

Mehmet Saglam

University of Cincinnati - Department of Finance - Real Estate

Jun Wu

Wharton Research Data Services (WRDS)

Date Written: September 21, 2023

Abstract

Researchers using samples of trades identified as retail by the Boehmer et al. (2021) methodology implicitly assume their data are representative of actual retail trades. Given the work of Barber et al. (2023), who find the algorithm only identifies 35% of trades they place with retail brokers, one must assume the sample of retail trades that is not classified as retail by the algorithm has the same characteristics as the sample of retail trades that are identified as retail. Moreover, researchers must either assume the algorithm does not falsely identify institutional trades to be retail or that institutional trades have the same characteristics as retail trades. We demonstrate that neither of these assumptions are valid in practice. Institutional order flow routinely trades on subpenny increments that are identified as retail. Furthermore, the subset of retail trades identified by the algorithm to be retail differs significantly along many dimensions from the subset of retail trades that are not classified as retail so that the stratified random samples of securities used by researchers do not accurately represent actual retail trading.

Keywords: Retail trades

JEL Classification: G20

Suggested Citation

Battalio, Robert H. and Jennings, Robert H. and Saglam, Mehmet and Wu, Jun, Difficulties in obtaining a representative sample of retail trades from public data sources (September 21, 2023). Available at SSRN: https://ssrn.com/abstract=4579159 or http://dx.doi.org/10.2139/ssrn.4579159

Robert H. Battalio (Contact Author)

University of Notre Dame - Department of Finance ( email )

P.O. Box 399
Notre Dame, IN 46556-0399
United States
574-631-9428 (Phone)
574-631-5255 (Fax)

Robert H. Jennings

Indiana University - Kelley School of Business - Department of Finance ( email )

1309 E. 10th St.
Bloomington, IN 47405
United States
812-855-2696 (Phone)
812-855-5875 (Fax)

Mehmet Saglam

University of Cincinnati - Department of Finance - Real Estate ( email )

Carl H. Lindner College of Business
Cincinnati, OH 45221
United States
(513) 556-9108 (Phone)

HOME PAGE: http://homepages.uc.edu/~saglammt/

Jun Wu

Wharton Research Data Services (WRDS) ( email )

3819 Chestnut St
Suite 300
Philadelphia, PA 19104
United States

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