Trading on Algos
40 Pages Posted: 2 Nov 2013 Last revised: 11 Jul 2017
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: Suggested Citation