Analysis and Modeling of Client Order Flow in Limit Order Markets

32 Pages Posted: 28 Feb 2022

See all articles by Rama Cont

Rama Cont

University of Oxford

Mihai Cucuringu

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

Vacslav Glukhov

JP Morgan

Felix Prenzel

University of Oxford - Mathematical Institute

Date Written: December 30, 2021

Abstract

Orders in major electronic stock markets are executed through centralised limit order books (LOBs). The availability of historical data have led to extensive research modelling LOBs. Better understanding the dynamics of LOBs and building simulators as a framework for controlled experiments, when testing trading algorithms or execution strategies are among the aims in this area. Most work in the literature models the aggregate view of the limit order book, which focuses on the volume of orders at a given price level using a point process. In addition to this aggregate view, brokers and exchanges also have information on the identity of the agents submitting the order to them. This leads to a more complicated representation of limit order book dynamics, which we attempt to model using a heterogeneous model of order flow.

We present a granular representation of the limit order book, that allows to account for the origins of different orders. Using client order flow from a large broker, we analyze the properties of variables in this representation. The heterogeneity of the order flow is modeled by segmenting clients into different clusters, for which we identify representative prototypes. This segmentation appears to be stable both over time, as well as over different stocks. Our findings can be leveraged to build more realistic order flow models that account for the diversity of market participants.

Keywords: Limit order books, order flow, heterogeneous order flow, unsupervised learning, clustering, time series, machine learning

Suggested Citation

Cont, Rama and Cucuringu, Mihai and Glukhov, Vacslav and Prenzel, Felix, Analysis and Modeling of Client Order Flow in Limit Order Markets (December 30, 2021). Available at SSRN: https://ssrn.com/abstract=3997109 or http://dx.doi.org/10.2139/ssrn.3997109

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

Vacslav Glukhov

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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