Algorithmic Trading and the Market for Liquidity

45 Pages Posted: 9 Feb 2012 Last revised: 12 Apr 2012

See all articles by Terrence Hendershott

Terrence Hendershott

University of California, Berkeley - Haas School of Business

Ryan Riordan

Queen's University - Smith School of Business; Ludwig-Maximilians-University Munich, Faculty of Business Administration (Munich School of Management)

Date Written: April 11, 2012

Abstract

We examine the role of algorithmic traders (AT) in liquidity supply and demand in the 30 DAX stocks on the Deutsche Boerse in January 2008. AT represent 52% of market order volume and 64% of nonmarketable limit order volume. AT more actively monitor market liquidity than human traders. AT consume liquidity when it is cheap, i.e., when the bid-ask quotes are narrow, and supply liquidity when it is expensive. When spreads are narrow AT are less likely to submit new orders, less likely to cancel their orders, and more likely to initiate trades. AT react more quickly to events and even more so when spreads are wide.

Keywords: algorithmic trading, liquidity, market monitoring

JEL Classification: G10, G14

Suggested Citation

Hendershott, Terrence J. and Riordan, Ryan, Algorithmic Trading and the Market for Liquidity (April 11, 2012). Journal of Financial and Quantitative Analysis (JFQA), Forthcoming, Available at SSRN: https://ssrn.com/abstract=2001912 or http://dx.doi.org/10.2139/ssrn.2001912

Terrence J. Hendershott

University of California, Berkeley - Haas School of Business ( email )

545 Student Services Building, #1900
2220 Piedmont Avenue
Berkeley, CA 94720
United States

Ryan Riordan (Contact Author)

Queen's University - Smith School of Business ( email )

Smith School of Business, Queen's University
143 Union Street
Kingston, Ontario K7L 3N6
Canada

Ludwig-Maximilians-University Munich, Faculty of Business Administration (Munich School of Management) ( email )

Schackstr. 4
Munich, 80539
Germany