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Modelling Equity Transaction Networks as Bursty Processes

Seabrook, Isobel; Barucca, Paolo; Caccioli, Fabio; (2022) Modelling Equity Transaction Networks as Bursty Processes. ArXiv: Ithaca, NY, USA. Green open access

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Abstract

Trade executions for major stocks come in bursts of activity, which can be partly attributed to the presence of self- and mutual excitations endogenous to the system. In this paper, we study transaction reports for five FTSE 100 stocks. We model the dynamic of transactions between counterparties using both univariate and multivariate Hawkes processes, which we fit to the data using a parametric approach. We find that the frequency of transactions between counterparties increases the likelihood of them to transact in the future, and that univariate and multivariate Hawkes processes show promise as generative models able to reproduce the bursty, hub dominated systems that we observe in the real world. We further show that Hawkes processes perform well when used to model buys and sells through a central clearing counterparty when considered as a bivariate process, but not when these are modelled as individual univariate processes, indicating that mutual excitation between buys and sells is present in these markets.

Type: Working / discussion paper
Title: Modelling Equity Transaction Networks as Bursty Processes
Open access status: An open access version is available from UCL Discovery
DOI: 10.48550/arXiv.2207.13696
Publisher version: https://doi.org/10.48550/arXiv.2207.13696
Language: English
Additional information: This is an Open Access paper published under a Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10182311
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