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We consider a sequence of Hawkes processes whose excitation measures may depend on the generation, and study its scaling limits in the near-unstable limiting regime. The limiting random measures, characterized via a nonlinear convolutional…

Probability · Mathematics 2026-04-08 Tristan Pace , Gordan Zitkovic

This paper investigates the asymptotic behavior of suitably time-modulated Hawkes processes with heavy-tailed kernels in a nearly unstable regime. We show that, under appropriate scaling, both the intensity processes and the rescaled Hawkes…

Probability · Mathematics 2026-02-12 Emmanuel Gnabeyeu , Gilles Pagès , Mathieu Rosenbaum

We consider the problem of estimating the parameters of a non-stationary Hawkes process with time-dependent reproduction rate and baseline intensity. Our approach relies on the standard maximum likelihood estimator (MLE), coinciding with…

Statistics Theory · Mathematics 2025-06-04 Thomas Deschatre , Pierre Gruet , Antoine Lotz

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

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

The propagation of chaos and associated law of large numbers for mean-field interacting age-dependent Hawkes processes (when the number of processes n goes to +$\infty$) being granted by the study performed in (Chevallier, 2015), the aim of…

Probability · Mathematics 2016-11-08 Julien Chevallier

We study probabilities of various rare events for the limiting point process that appears at the random matrix hard edge. We also show a transition from hard edge to bulk behavior. Asymptotic events studied include a central limit theorem…

Probability · Mathematics 2017-11-22 Diane Holcomb

Fueled in part by recent applications in neuroscience, the multivariate Hawkes process has become a popular tool for modeling the network of interactions among high-dimensional point process data. While evaluating the uncertainty of the…

Machine Learning · Statistics 2020-07-16 Xu Wang , Mladen Kolar , Ali Shojaie

This article presents a Hawkes process model with Markovian baseline intensities for high-frequency order book data modeling. We classify intraday order book trading events into a range of categories based on their order types and the price…

Trading and Market Microstructure · Quantitative Finance 2022-01-07 Philip Protter , Qianfan Wu , Shihao Yang

Hawkes Processes capture self-excitation and mutual-excitation between events when the arrival of an event makes future events more likely to happen. Identification of such temporal covariance can reveal the underlying structure to better…

Machine Learning · Computer Science 2020-06-03 Rafael Lima , Jaesik Choi

The neural Hawkes process (Mei & Eisner, 2017) is a generative model of irregularly spaced sequences of discrete events. To handle complex domains with many event types, Mei et al. (2020a) further consider a setting in which each event in…

Machine Learning · Computer Science 2022-05-09 Chenghao Yang , Hongyuan Mei , Jason Eisner

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

We study Markov chains formed by squared singular values of products of truncated orthogonal, unitary, symplectic matrices (corresponding to the Dyson index $\beta = 1,2,4$ respectively) where time corresponds to the number of terms in the…

Probability · Mathematics 2020-07-14 Andrew Ahn

This paper studies: (i) the long time behaviour of the empirical distribution of age and normalised position of an age dependent critical branching Markov process conditioned on non-extinction; and (ii) the super-process limit of a sequence…

Probability · Mathematics 2007-05-23 Krishna Athreya , Siva Athreya , Srikanth Iyer

The paper studies an improved estimate for the rate of convergence for nonlinear homogeneous discrete-time Markov chains. These processes are nonlinear in terms of the distribution law. Hence, the transition kernels are dependent on the…

Probability · Mathematics 2021-05-21 Aleksandr Shchegolev

Motivated by applications to COVID dynamics, we describe a branching process in random environments model $\{Z_n\}$ whose characteristics change when crossing upper and lower thresholds. This introduces a cyclical path behavior involving…

Probability · Mathematics 2026-01-14 Giacomo Francisci , Anand N. Vidyashankar

Let $\left\{ Z_{n},n=0,1,2,...\right\} $ be a critical branching process in random environment and let $\left\{ S_{n},n=0,1,2,...\right\} $ be its associated random walk. It is known that if the increments of this random walk belong…

Probability · Mathematics 2022-09-29 Vladimir Vatutin , Elena Dyakonova

We study a catalytic branching process (CBP) with any finite set of catalysts. This model describes a system of particles where the movement is governed by a Markov chain with arbitrary finite or countable state space and the branching may…

Probability · Mathematics 2016-03-18 Ekaterina Vl. Bulinskaya

Temporal point processes (TPP) are a natural tool for modeling event-based data. Among all TPP models, Hawkes processes have proven to be the most widely used, mainly due to their adequate modeling for various applications, particularly…

Machine Learning · Statistics 2023-08-03 Guillaume Staerman , Cédric Allain , Alexandre Gramfort , Thomas Moreau

Multivariate Hawkes processes are a widely used class of self-exciting point processes, but maximum likelihood estimation naively scales as $O(N^2)$ in the number of events. The canonical linear exponential Hawkes process admits a faster…

Machine Learning · Computer Science 2026-05-07 Ahmer Raza , Hudson Smith