Limit Order Book Simulation with Generative Adversarial Networks

28 Pages Posted: 24 Jul 2023

See all articles by Rama Cont

Rama Cont

University of Oxford

Mihai Cucuringu

University of Oxford - Department of Statistics; The Alan Turing Institute

Jonathan Kochems

JP Morgan

Felix Prenzel

University of Oxford - Mathematical Institute

Date Written: July 16, 2023

Abstract

We propose a nonparametric method for simulating the dynamics of a limit order book using Generative Adversarial Networks (GAN) to learn the conditional distribution of the future state of the order book given its current state from time series of the limit order book. Our method yields a scenario generator for limit order books which captures a range of stylized facts and salient properties of limit order book transitions. We show that the trained generator is also able to correctly reproduce some key properties observed in empirical studies on market impact. In particular, the model exhibits a decaying marginal impact of trade size, higher impact of aggressive orders, as well as a decreasing relation between impact and order book depth.

Keywords: Generative Modeling, GANs, Limit Order Books, Market Impact, Synthetic Data

JEL Classification: C63, C58, G10

Suggested Citation

Cont, Rama and Cucuringu, Mihai and Kochems, Jonathan and Prenzel, Felix, Limit Order Book Simulation with Generative Adversarial Networks (July 16, 2023). Available at SSRN: https://ssrn.com/abstract=4512356 or http://dx.doi.org/10.2139/ssrn.4512356

Rama Cont

University of Oxford ( email )

Mathematical Institute
Oxford, OX2 6GG
United Kingdom

HOME PAGE: http://www.maths.ox.ac.uk/people/rama.cont

Mihai Cucuringu

University of Oxford - Department of Statistics ( email )

24-29 St Giles
Oxford
United Kingdom

HOME PAGE: http://https://www.stats.ox.ac.uk/~cucuring/

The Alan Turing Institute ( email )

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

Jonathan Kochems

JP Morgan ( email )

London
United Kingdom

Felix Prenzel (Contact Author)

University of Oxford - Mathematical Institute ( email )

Radcliffe Observatory, Andrew Wiles Building
Woodstock Rd
Oxford, Oxfordshire OX2 6GG
United Kingdom

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