Algorithmic trading and market quality: International evidence

• Main Authors: BOEHMER, Ekkehart, FONG, Kingsley, WU, Juan Julie
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Algorithmic trading; market quality; high frequency trading; buy-side institution; execution costs; Corporate Finance; Finance and Financial Management
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/6685; https://ink.library.smu.edu.sg/context/lkcsb_research/article/7684/viewcontent/AT_Sep2019_sv.pdf
• Institution: Singapore Management University

We study the effect of algorithmic trading (AT) on market quality between 2001 and 2011 in 42 equity markets around the world. We use an exchange colocation service that increases AT as an exogenous instrument to draw causal inferences about AT on market quality. On average, AT improves liquidity and informational efficiency but increases short-term volatility. Importantly, 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.