Imperial College London

DrMikkoPakkanen

Faculty of Natural SciencesDepartment of Mathematics

Reader in Data Science and Quantitative Finance
 
 
 
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Contact

 

+44 (0)20 7594 8541m.pakkanen Website

 
 
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Location

 

809Weeks BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Morariu-Patrichi:2022,
author = {Morariu-Patrichi, M and Pakkanen, MS},
journal = {Quantitative Finance},
pages = {563--583},
title = {State-dependent Hawkes processes and their application to limit order book modelling},
url = {http://hdl.handle.net/10044/1/91711},
volume = {22},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - We study statistical aspects of state-dependent Hawkes processes, which are an extension of Hawkesprocesses where a self- and cross-exciting counting process and a state process are fully coupled, interacting with each other. The excitation kernel of the counting process depends on the state process that,reciprocally, switches state when there is an event in the counting process. We first establish the existenceand uniqueness of state-dependent Hawkes processes and explain how they can be simulated. Then wedevelop maximum likelihood estimation methodology for parametric specifications of the process. Weapply state-dependent Hawkes processes to high-frequency limit order book data, allowing us to builda novel model that captures the feedback loop between the order flow and the shape of the limit orderbook. We estimate two specifications of the model, using the bid–ask spread and the queue imbalanceas state variables, and find that excitation effects in the order flow are strongly state-dependent. Additionally, we find that the endogeneity of the order flow, measured by the magnitude of excitation, is alsostate-dependent, being more pronounced in disequilibrium states of the limit order book.
AU - Morariu-Patrichi,M
AU - Pakkanen,MS
EP - 583
PY - 2022///
SN - 1469-7688
SP - 563
TI - State-dependent Hawkes processes and their application to limit order book modelling
T2 - Quantitative Finance
UR - http://hdl.handle.net/10044/1/91711
VL - 22
ER -