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We establish the weak convergence of the intensity of a nearly-unstable Hawkes process with heavy-tailed kernel. Our result is used to derive a scaling limit for a financial market model where orders to buy or sell an asset arrive according…

Mathematical Finance · Quantitative Finance 2026-03-26 Ulrich Horst , Wei Xu , Rouyi Zhang

Multivariate Hawkes process provides a powerful framework for modeling temporal dependencies and event-driven interactions in complex systems. While existing methods primarily focus on uncovering causal structures among observed…

Machine Learning · Computer Science 2026-03-03 Songyao Jin , Biwei Huang

Hawkes process is a class of simple point processes with self-exciting and clustering properties. Hawkes process has been widely applied in finance, neuroscience, social networks, criminology, seismology, and many other fields. In this…

Probability · Mathematics 2020-11-23 Fuqing Gao , Lingjiong Zhu

We prove central limit theorems (CLT) for empirical processes of extreme values cluster functionals as in Drees and Rootz\'en (2010). We use coupling properties enlightened for Dedecker \& Prieur's $\tau-$dependence coefficients in order to…

Probability · Mathematics 2016-02-29 Paul Doukhan , José Gregorio Gómez

In this paper, we propose an extension of the Hawkes process by incorporating a kernel based on the tempered Mittag-Leffler distribution. This is the generalization of the work presented in [10]. We derive analytical results for the…

Probability · Mathematics 2024-08-22 Neha Gupta , Aditya Maheshwari

Nowadays a vast literature is available on the Hele-Shaw or incompressible limit for nonlinear degenerate diffusion equations. This problem has attracted a lot of attention due to its applications to tissue growth and crowd motion modelling…

Analysis of PDEs · Mathematics 2025-10-29 Noemi David , Alpár R. Mészáros , Filippo Santambrogio

For a uniform process $\{ X_t: t\in E\}$ (by which $X_t $ is uniformly distributed on $(0,1)$ for $t\in E$) and a function $w(x)>0$ on $(0,1)$, we give a sufficient condition for the weak convergence of the empirical process based on $\{…

Probability · Mathematics 2014-12-30 Yuping Yang

In this paper, we prove a process-level, also known as level-3 large deviation principle for a very general class of simple point processes, i.e. nonlinear Hawkes process, with a rate function given by the process-level entropy, which has…

Probability · Mathematics 2014-10-16 Lingjiong Zhu

In this paper, we establish sharp upper and lower bounds on the convergence rate of the empirical measures of point processes under the Wasserstein distance. To this end, we first introduce a new metric on the space of counting measures…

Statistics Theory · Mathematics 2026-04-28 Dongzhou Huang , Tianyi Jiang , Haonan Wang

In this paper, we establish a central limit theorem for a large class of general supercritical superprocesses with spatially dependent branching mechanisms satisfying a second moment condition. This central limit theorem generalizes and…

Probability · Mathematics 2014-09-22 Yan-Xia Ren , Renming Song , Rui Zhang

We develop a Bayesian nonparametric framework for inference in spatio-temporal Hawkes processes, extending existing theoretical results beyond the purely temporal setting. Our framework encompasses modelling both the background and…

Statistics Theory · Mathematics 2026-01-08 Xenia Miscouridou , Deborah Sulem

Constraint based causal structure learning for point processes require empirical tests of local independence. Existing tests require strong model assumptions, e.g. that the true data generating model is a Hawkes process with no latent…

Methodology · Statistics 2021-10-26 Nikolaj Thams , Niels Richard Hansen

This paper derives non-asymptotic error bounds for nonlinear stochastic approximation algorithms in the Wasserstein-$p$ distance. To obtain explicit finite-sample guarantees for the last iterate, we develop a coupling argument that compares…

Machine Learning · Computer Science 2026-02-03 Seo Taek Kong , R. Srikant

We establish the asymptotic validity of frequency-domain inference for stationary multivariate Hawkes processes under mild conditions, bridging the gap between theory and application. By developing upper-bounds on the reduced cumulant…

Statistics Theory · Mathematics 2026-04-14 Yifu Tang , Conor Kresin , Boris Baeumer , Ting Wang

We address the problem of proving a Central Limit Theorem for the empirical optimal transport cost, $\sqrt{n}\{\mathcal{T}_c(P_n,Q)-\mathcal{W}_c(P,Q)\}$, in the semi discrete case, i.e when the distribution $P$ is finitely supported. We…

Probability · Mathematics 2021-05-26 Eustasio del Barrio , Alberto González-Sanz , Jean-Michel Loubes

Bessel processes $(X_{t,k})_{t\ge0}$ in $N$ dimensions are classified via associated root systems and multiplicity constants $k\ge0$. They describe interacting Calogero-Moser-Suther\-land particle systems with $N$ particles and are related…

Probability · Mathematics 2021-05-20 Sergio Andraus , Michael Voit

In this paper, we establish the asymptotic behavior of {\it supercritical} nearly unstable Hawkes processes with a power law kernel. We find that, the Hawkes process in our context admits a similar equation to that in \cite{MR3563196} for…

Probability · Mathematics 2025-04-25 Liping Xu , An Zhang

We establish limit theorems involving weak convergence of multiple generations of critical and supercritical branching processes. These results arise naturally when dealing with the joint asymptotic behavior of functionals defined in terms…

Probability · Mathematics 2009-12-25 James Kuelbs , Anand N. Vidyashankar

We prove error bounds in a central limit theorem for solutions of certain convolution equations. The main motivation for investigating these equations stems from applications to lace expansions, in particular to weakly self-avoiding random…

Probability · Mathematics 2014-04-11 Luca Avena , Erwin Bolthausen , Christine Ritzmann

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
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