A Limit Order Book Model for Latency Arbitrage

28 Pages Posted: 21 Oct 2011

See all articles by Samuel N. Cohen

Samuel N. Cohen

University of Oxford - Mathematical Institute; The Alan Turing Institute

Lukasz Szpruch

University of Edinburgh - School of Mathematics; The Alan Turing Institute; Simtopia

Date Written: October 21, 2011

Abstract

We consider a single security market based on a limit order book and two investors, with different speeds of trade execution. If the fast investor can front-run the slower investor, we show that this allows the fast trader to obtain risk free profits, but that these profits cannot be scaled. We derive the fast trader's optimal behaviour when she has only distributional knowledge of the slow trader's actions, with few restrictions on the possible prior distributions. We also consider the slower trader's response to the presence of a fast trader in a market, and the effects of the introduction of a 'Tobin tax' on financial transactions. We show that such a tax can lead to the elimination of profits from front-running strategies. Consequently, a Tobin tax can both increase market efficiency and attract traders to a market.

Keywords: limit order book, latency arbitrage, high-frequency trading, Tobin tax

Suggested Citation

Cohen, Samuel N. and Szpruch, Lukasz, A Limit Order Book Model for Latency Arbitrage (October 21, 2011). Available at SSRN: https://ssrn.com/abstract=1947328 or http://dx.doi.org/10.2139/ssrn.1947328

Samuel N. Cohen (Contact Author)

University of Oxford - Mathematical Institute ( email )

Woodstock Road
Oxford, Oxfordshire OX26GG
United Kingdom

The Alan Turing Institute ( email )

British Library
96 Euston Road
London, NW1 2DB
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Lukasz Szpruch

University of Edinburgh - School of Mathematics ( email )

James Clerk Maxwell Building
Peter Guthrie Tait Rd
Edinburgh, EH9 3FD
United Kingdom

The Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

Simtopia ( email )

United Kingdom

HOME PAGE: http://https://www.simtopia.ai

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