Algorithmic Trading and Firm Value

51 Pages Posted: 5 Apr 2014 Last revised: 16 Aug 2019

See all articles by Brian C. Hatch

Brian C. Hatch

University of Cincinnati - Department of Finance - Real Estate

Shane A. Johnson

Texas A&M University - Department of Finance

Jun Zhang

Oklahoma State University

Date Written: August 13, 2019

Abstract

Using data from 2002 to 2013, we examine the impact of algorithmic trading on firm value. The results show that algorithmic trading generates net benefits for firm value through impacting stock liquidity, idiosyncratic volatility, and idiosyncratic skewness, and firms benefit more from algorithmic trading when algorithmic trading intensity is higher. Using the advent of auto quotation on the New York Stock Exchange as an exogenous shock to algorithmic trading, we find evidence of a causal effect of algorithmic trading on firm value through channels of stock liquidity, idiosyncratic volatility, and idiosyncratic skewness. The positive effects of algorithmic trading on firm value are stronger for firms with higher stock liquidity, for larger firms, and in the post-2007 period when algorithmic trading intensity is higher.

Keywords: Algorithmic trading; Stock liquidity; Firm value

JEL Classification: G12, G14, G32

Suggested Citation

Hatch, Brian C. and Johnson, Shane A. and Zhang, Jun, Algorithmic Trading and Firm Value (August 13, 2019). Available at SSRN: https://ssrn.com/abstract=2420017 or http://dx.doi.org/10.2139/ssrn.2420017

Brian C. Hatch

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

Carl H. Lindner Hall
P.O. Box 210195
Cincinnati, OH 45221
United States
513-556-7076 (Phone)
513-556-0979 (Fax)

Shane A. Johnson (Contact Author)

Texas A&M University - Department of Finance ( email )

Mays School of Business
College Station, TX 77843-4218
United States
979-862-3318 (Phone)

Jun Zhang

Oklahoma State University ( email )

201 Business
Stillwater, OK 74078-0555
United States

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