Functional limit theorems for nonstationary marked Hawkes processes in the high intensity regime

  • Bo Li
  • , Guodong Pang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We study marked Hawkes processes with an intensity process which has a non-stationary baseline intensity, a general self-exciting function of event “ages” at each time and marks. The marks are assumed to be conditionally independent given the event times, while the distribution of each mark depends on the event time, that is, time-varying. We first observe an immigration–birth (branching) representation of such a non-stationary marked Hawkes process, and then derive an equivalent representation of the process using the associated conditional inhomogeneous Poisson processes with stochastic intensities. We consider such a Hawkes process in the high intensity regime, where the baseline intensity gets large, while the self-exciting function and distributions of the marks are unscaled, and there is no time-scaling in the scaled Hawkes process. We prove functional law of large numbers and functional central limit theorems (FCLTs) for the scaled Hawkes processes in this asymptotic regime. The limits in the FCLTs are characterized by continuous Gaussian processes with covariance structures expressed with convolution functionals resulting from the branching representation. We also consider the special cases of multiplicative self-exciting functions, and an indicator type of non-decomposable self-exciting functions (including the cases of “ceasing” and “delayed” reproductions as well as their extensions with varying reproduction rates), and study the properties of the limiting Gaussian processes in these special cases.

Original languageEnglish (US)
Pages (from-to)285-339
Number of pages55
JournalStochastic Processes and their Applications
Volume143
DOIs
StatePublished - Jan 2022

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Applied Mathematics

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