Hawkes Models And Their Applications
Abstract
The Hawkes process is a model for counting the number of arrivals to a system which exhibits the self-exciting property - that one arrival creates a heightened chance of further arrivals in the near future. The model, and its generalizations, have been applied in a plethora of disparate domains, though two particularly developed applications are in seismology and in finance. As the original model is elegantly simple, generalizations have been proposed which: track marks for each arrival, are multivariate, have a spatial component, are driven by renewal processes, treat time as discrete, and so on. This paper creates a cohesive review of the traditional Hawkes model and the modern generalizations, providing details on their construction, simulation algorithms, and giving key references to the appropriate literature for a detailed treatment.
Keywords
Cite
@article{arxiv.2405.10527,
title = {Hawkes Models And Their Applications},
author = {Patrick J. Laub and Young Lee and Philip K. Pollett and Thomas Taimre},
journal= {arXiv preprint arXiv:2405.10527},
year = {2024}
}