Limit Order Book Dynamics and Order Size Modelling Using Compound Hawkes Process

Fuente: arXiv
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Autori principali: Jain, Konark, Firoozye, Nick, Kochems, Jonathan, Treleaven, Philip
Natura: Preprint
Pubblicazione: 2023
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author Jain, Konark
Firoozye, Nick
Kochems, Jonathan
Treleaven, Philip
author_facet Jain, Konark
Firoozye, Nick
Kochems, Jonathan
Treleaven, Philip
contents Hawkes Process has been used to model Limit Order Book (LOB) dynamics in several ways in the literature however the focus has been limited to capturing the inter-event times while the order size is usually assumed to be constant. We propose a novel methodology of using Compound Hawkes Process for the LOB where each event has an order size sampled from a calibrated distribution. The process is formulated in a novel way such that the spread of the process always remains positive. Further, we condition the model parameters on time of day to support empirical observations. We make use of an enhanced non-parametric method to calibrate the Hawkes kernels and allow for inhibitory cross-excitation kernels. We showcase the results and quality of fits for an equity stock's LOB in the NASDAQ exchange and compare them against several baselines. Finally, we conduct a market impact study of the simulator and show the empirical observation of a concave market impact function is indeed replicated.
format Preprint
id arxiv_https___arxiv_org_abs_2312_08927
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Limit Order Book Dynamics and Order Size Modelling Using Compound Hawkes Process
Jain, Konark
Firoozye, Nick
Kochems, Jonathan
Treleaven, Philip
Trading and Market Microstructure
Computational Engineering, Finance, and Science
Computational Finance
Applications
Hawkes Process has been used to model Limit Order Book (LOB) dynamics in several ways in the literature however the focus has been limited to capturing the inter-event times while the order size is usually assumed to be constant. We propose a novel methodology of using Compound Hawkes Process for the LOB where each event has an order size sampled from a calibrated distribution. The process is formulated in a novel way such that the spread of the process always remains positive. Further, we condition the model parameters on time of day to support empirical observations. We make use of an enhanced non-parametric method to calibrate the Hawkes kernels and allow for inhibitory cross-excitation kernels. We showcase the results and quality of fits for an equity stock's LOB in the NASDAQ exchange and compare them against several baselines. Finally, we conduct a market impact study of the simulator and show the empirical observation of a concave market impact function is indeed replicated.
title Limit Order Book Dynamics and Order Size Modelling Using Compound Hawkes Process
topic Trading and Market Microstructure
Computational Engineering, Finance, and Science
Computational Finance
Applications
url https://arxiv.org/abs/2312.08927