Hawkes processes are a particularly interesting class of stochastic point processes that were introduced in the early seventies by Alan Hawkes, notably to model the occurrence of seismic events. They are also called self-exciting point processes, in which the occurrence of an event increases the probability of occurrence of another event. The Hawkes process is characterized by a stochastic intensity, which represents the conditional probability density of the occurrence of an event in the immediate future, given the observations in the past. In this paper, we present some background and all major aspects of Hawkes processes, with a particular focus on simulation methods, and estimation techniques widely used in practical modeling aspects. We aim to provide a rich and self-contained overview of these stochastic processes as a way to have an overall vision of Hawkes processes in only one piece of paper. We also discuss possibilities for future research in the area of self-exciting processes.
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Umea Univ, Dept Math & Math Stat, Umea, SwedenUmea Univ, Dept Math & Math Stat, Umea, Sweden
Ghorbani, Mohammad
Cronie, Ottmar
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Umea Univ, Dept Math & Math Stat, Umea, Sweden
Univ Gothenburg, Sch Publ Hlth & Community Med, Inst Med, Biostat, Gothenburg, SwedenUmea Univ, Dept Math & Math Stat, Umea, Sweden
Cronie, Ottmar
Mateu, Jorge
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Univ Jaume 1, Dept Math, Castellon de La Plana, SpainUmea Univ, Dept Math & Math Stat, Umea, Sweden
Mateu, Jorge
Yu, Jun
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Umea Univ, Dept Math & Math Stat, Umea, SwedenUmea Univ, Dept Math & Math Stat, Umea, Sweden