Back-Running: Seeking and Hiding Fundamental Information in Order Flows

64 Pages Posted: 24 Mar 2015 Last revised: 21 Nov 2018

See all articles by Liyan Yang

Liyan Yang

University of Toronto - Rotman School of Management

Haoxiang Zhu

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER)

Date Written: November 20, 2018

Abstract

We model the strategic interaction between fundamental investors and ``back-runners,'' whose only information is about past order flows of fundamental investors. Back-runners partly infer fundamental investors' information from order flows and exploit it in subsequent trading. Fundamental investors counteract by randomizing their order execution, unless back-runners' signals are highly imprecise. Somewhat surprisingly, a higher accuracy of back-runners' order flow information can harm back-runners and benefit fundamental investors. The prediction that back-runners eventually trade in the same direction as fundamental investors is supported by recent evidence. We also calibrate the model to estimate the profits of back-runners if their information is derived from payment for retail order flow.

Keywords: back-running, order flow, order anticipation, high-frequency trading, price discovery, market liquidity, payment for order flow

JEL Classification: G14, G18

Suggested Citation

Yang, Liyan and Zhu, Haoxiang, Back-Running: Seeking and Hiding Fundamental Information in Order Flows (November 20, 2018). Rotman School of Management Working Paper No. 2583915. Available at SSRN: https://ssrn.com/abstract=2583915 or http://dx.doi.org/10.2139/ssrn.2583915

Liyan Yang

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada

Haoxiang Zhu (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street E62-623
Cambridge, MA 02142
United States

HOME PAGE: http://www.mit.edu/~zhuh

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
1,496
rank
10,927
Abstract Views
5,366
PlumX Metrics