Algorithmic Trading and Market Quality: International Evidence

45 Pages Posted: 15 Mar 2012 Last revised: 8 Aug 2018

See all articles by Ekkehart Boehmer

Ekkehart Boehmer

Singapore Management University - Lee Kong Chian School of Business

Kingsley Y. L. Fong

University of New South Wales - School of Banking and Finance; Financial Research Network (FIRN)

Julie Wu

University of Nebraska - Lincoln

Date Written: 2018

Abstract

We study the effect of algorithmic trading (AT) on market quality between 2001 and 2011 in 42 equity markets around the world. We use exchange co-location service that increases AT as an exogenous instrument to draw causal inference of AT on market quality. On average, AT improves liquidity and informational efficiency but increases short-term volatility. AT also lowers execution shortfalls for buy-side institutional investors. Our results are surprisingly consistent across markets and thus across a wide range of AT environments. We further document that the beneficial effect of AT is stronger in large stocks than in small stocks.

Keywords: Algorithmic trading, high frequency trading, market structure

JEL Classification: G19, G15

Suggested Citation

Boehmer, Ekkehart and Fong, Kingsley Y. L. and Wu, Julie, Algorithmic Trading and Market Quality: International Evidence (2018). AFA 2013 San Diego Meetings Paper. Available at SSRN: https://ssrn.com/abstract=2022034 or http://dx.doi.org/10.2139/ssrn.2022034

Ekkehart Boehmer (Contact Author)

Singapore Management University - Lee Kong Chian School of Business ( email )

Singapore

Kingsley Y. L. Fong

University of New South Wales - School of Banking and Finance ( email )

Sydney, NSW 2052
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Julie Wu

University of Nebraska - Lincoln ( email )

Lincoln, NE 68588
United States

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