The Simplicity of Optimal Trading in Order Book Markets

24 Pages Posted: 21 Mar 2014

See all articles by Daniel Ladley

Daniel Ladley

University of Leicester - School of Business

Paolo Pellizzari

Ca Foscari University of Venice - Dipartimento di Economia

Date Written: February 20, 2014

Abstract

A trader's execution strategy has a large effect on his profits. Identifying an optimal strategy, however, is often frustrated by the complexity of market microstructure's. We analyse an order book based continuous double auction market under two different models of trader's behaviour. In the first case actions only depend on a linear combination of the best bid and ask. In the second model traders adopt the Markov perfect equilibrium strategies of the trading game. Both models are analytically intractable and so optimal strategies are identified by the use of numerical techniques. Using the Markov model we show that, beyond the best quotes, additional information has little effect on either the behaviour of traders or the dynamics of the market. The remarkable similarity of the results obtained by the linear model indicates that the optimal strategy may be reasonably approximated by a linear function. We conclude that whilst the order book market and strategy space of traders are potentially very large and complex, optimal strategies may be relatively simple and based on a minimal information set.

Keywords: Continuous Double Auction, Order Book, Information, Optimal Trading

JEL Classification: D44, G10, C63

Suggested Citation

Ladley, Daniel and Pellizzari, Paolo, The Simplicity of Optimal Trading in Order Book Markets (February 20, 2014). Department of Management, Università Ca' Foscari Venezia Working Paper No. 05/WP/2014, Available at SSRN: https://ssrn.com/abstract=2411983 or http://dx.doi.org/10.2139/ssrn.2411983

Daniel Ladley

University of Leicester - School of Business ( email )

University Road
Leicester, LE1 7RH
United Kingdom

Paolo Pellizzari (Contact Author)

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
244
Abstract Views
1,240
rank
138,867
PlumX Metrics