Trading on Algos

40 Pages Posted: 2 Nov 2013 Last revised: 11 Jul 2017

See all articles by Johannes Atle Skjeltorp

Johannes Atle Skjeltorp

Central Bank of Norway

Elvira Sojli

University of New South Wales (UNSW); UNSW Business School

Wing Wah Tham

University of New South Wales (UNSW)

Date Written: July 31, 2015

Abstract

This paper studies the impact of algorithmic trading (AT) on asset prices. We find that the heterogeneity of algorithmic traders across stocks generates predictable patterns in stock returns. A trading strategy that exploits the AT return predictability generates a monthly risk-adjusted performance between 50-130 basis points for the period 1999 to 2012. We find that stocks with lower AT have higher returns, after controlling for standard market-, size-, book-to-market-, momentum, and liquidity risk factors. This effect survives the inclusion of many cross-sectional return predictors and is statistically and economically significant. Return predictability is stronger among stocks with higher impediments to trade and higher predatory/opportunistic algorithmic traders. Our paper is the first to study and establish a strong link between algorithmic trading and asset prices.

Keywords: Asset pricing, Algorithmic trading, High frequency trading, Market quality, Liquidity

JEL Classification: G10; G20; G14

Suggested Citation

Skjeltorp, Johannes Atle and Sojli, Elvira and Tham, Wing Wah, Trading on Algos (July 31, 2015). Available at SSRN: https://ssrn.com/abstract=2348418 or http://dx.doi.org/10.2139/ssrn.2348418

Johannes Atle Skjeltorp

Central Bank of Norway ( email )

P.O. Box 1179
Oslo, N-0107
Norway

HOME PAGE: http://www.norges-bank.no/research/skjeltorp/

Elvira Sojli (Contact Author)

University of New South Wales (UNSW) ( email )

Kensington
High St
Sydney, NSW 2052
Australia

HOME PAGE: http://https://sites.google.com/site/esojli/

UNSW Business School ( email )

Sydney, NSW 2052
Australia

HOME PAGE: http://sites.google.com/site/esojli/

Wing Wah Tham

University of New South Wales (UNSW)

Kensington
High St
Sydney, NSW 2052
Australia

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