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Related papers: On Stability of Hawkes Process

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Hawkes point processes are first-order non-Markovian stochastic models of intermittent bursty dynamics with applications to physical, seismic, epidemic, biological, financial, and social systems. While accounting for positive feedback loops…

Statistical Mechanics · Physics 2023-02-02 Kiyoshi Kanazawa , Didier Sornette

We propose a simulation method for multidimensional Hawkes processes based on superposition theory of point processes. This formulation allows us to design efficient simulations for Hawkes processes with differing exponentially decaying…

Machine Learning · Statistics 2018-03-14 Kar Wai Lim , Young Lee , Leif Hanlen , Hongbiao Zhao

We propose an extension to Hawkes processes by treating the levels of self-excitation as a stochastic differential equation. Our new point process allows better approximation in application domains where events and intensities accelerate…

Machine Learning · Computer Science 2016-09-23 Young Lee , Kar Wai Lim , Cheng Soon Ong

Both Hawkes processes and autoregressive processes rely on linear functionals of their past, while modeling different types of data. Since datasets arising from observations of the same phenomenon may be heterogeneous and sampled at…

Probability · Mathematics 2026-05-28 Théo Leblanc

The Hawkes process is a popular point process model for event sequences that exhibit temporal clustering. The intensity process of a Hawkes process consists of two components, the baseline intensity and the accumulated excitation effect due…

Statistics Theory · Mathematics 2024-08-20 Tsz-Kit Jeffrey Kwan , Feng Chen , William Dunsmuir

The Hawkes process, a self-exciting point process, has a wide range of applications in modeling earthquakes, social networks and stock markets. The established estimation process requires that researchers have access to the exact time…

Methodology · Statistics 2024-11-15 Lingxiao Zhou , Georgia Papadogeorgou

In the last decade, Hawkes processes have received a lot of attention as good models for functional connectivity in neural spiking networks. In this paper we consider a variant of this process, the Age Dependent Hawkes process, which…

Probability · Mathematics 2019-10-08 Mads Bonde Raad , Susanne Ditlevsen , Eva Löcherbach

Hawkes processes are a class of simple point processes that are self-exciting and have clustering effect, with wide applications in finance, social networks and many other fields. This paper considers a self-exciting Hawkes process where…

Trading and Market Microstructure · Quantitative Finance 2018-01-10 Xuefeng Gao , Xiang Zhou , Lingjiong Zhu

The Hawkes self-excited point process provides an efficient representation of the bursty intermittent dynamics of many physical, biological, geological and economic systems. By expressing the probability for the next event per unit time…

Statistical Mechanics · Physics 2020-09-23 Kiyoshi Kanazawa , Didier Sornette

We provide probabilistic and computational results on Markovian multivariate Hawkes processes and induced population processes. By applying the Markov property, we characterize in closed form a joint transform, bijective to the probability…

Probability · Mathematics 2025-08-08 R. S. Karim , R. J. A. Laeven , M , M. Mandjes

We study a multivariate Hawkes process with long-range interactions, where the interaction strength decays as a power-law in the distance of the particles with exponent $1+\alpha.$ Our main focus is on the long-time asymptotic behavior of…

Probability · Mathematics 2026-03-09 Nadia Belmabrouk

A univariate Hawkes process is a simple point process that is self-exciting and has clustering effect. The intensity of this point process is given by the sum of a baseline intensity and another term that depends on the entire past history…

Probability · Mathematics 2018-10-04 Xuefeng Gao , Lingjiong Zhu

In this paper, we use the Hawkes process to model the sequence of failure, i.e., events of compressor station and conduct survival analysis on various failure events of the compressor station. However, until now, nearly all relevant…

Machine Learning · Computer Science 2021-12-28 Lu-ning Zhang , Jian-wei Liu , Xin Zuo

Multivariate Hawkes Processes (MHPs) are an important class of temporal point processes that have enabled key advances in understanding and predicting social information systems. However, due to their complex modeling of temporal…

Machine Learning · Computer Science 2020-03-02 Maximilian Nickel , Matthew Le

We generalise the construction of multivariate Hawkes processes to a possibly infinite network of counting processes on a directed graph $\mathbb G$. The process is constructed as the solution to a system of Poisson driven stochastic…

Probability · Mathematics 2014-03-25 Sylvain Delattre , Nicolas Fournier , Marc Hoffmann

Many events occur in the world. Some event types are stochastically excited or inhibited---in the sense of having their probabilities elevated or decreased---by patterns in the sequence of previous events. Discovering such patterns can help…

Machine Learning · Computer Science 2017-11-22 Hongyuan Mei , Jason Eisner

Modelling and forecasting the occurrence of extreme events is especially difficult when the event process is nonstationary, with changes in both the rate at which extremes occur and the magnitude of the extremes when they occur. We approach…

Methodology · Statistics 2026-05-06 Gordon J. Ross , Dean Markwick

In this paper we develop the first perfect sampling algorithm for queues with Hawkes input, i.e. single-server queues with Hawkes arrivals and i.i.d. service times of general distribution. In addition to the stability condition, we also…

Probability · Mathematics 2020-03-03 Xinyun Chen

We characterize a Hawkes point process with kernel proportional to the probability density function of Mittag-Leffler random variables. This kernel decays as a power law with exponent $\beta +1 \in (1,2]$. Several analytical results can be…

We propose a fast and efficient estimation method that is able to accurately recover the parameters of a d-dimensional Hawkes point-process from a set of observations. We exploit a mean-field approximation that is valid when the…

Machine Learning · Computer Science 2016-04-20 Emmanuel Bacry , Stéphane Gaïffas , Iacopo Mastromatteo , Jean-François Muzy