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Related papers: A note on critical Hawkes processes

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We analyze simple random walk on a supercritical Galton-Watson tree, where the walk is conditioned to return to the root at time $2n$. Specifically, we establish the asymptotic order (up to a constant factor) as $n\to\infty$, of the maximal…

Probability · Mathematics 2019-04-17 Josh Rosenberg

We show that random walk on the incipient infinite cluster (IIC) of two-dimensional critical percolation is subdiffusive in the chemical distance (i.e., in the intrinsic graph metric). Kesten (1986) famously showed that this is true for the…

Probability · Mathematics 2021-07-23 Shirshendu Ganguly , James R. Lee

We consider a supercritical symmetric continuous-time branching random walk on a multidimensional lattice with a finite number of particle generation sources of varying positive intensities without any restrictions on the variance of jumps…

Probability · Mathematics 2019-04-03 Ivan Khristolyubov , Elena Yarovaya

The jump processes W(t) on [0,\infty[ with transitions w -> alpha w at rate b*w^beta (0 =< alpha =< 1, b>0, beta>0) are considered. Their moments are shown to decay not faster than algebraically for t -> \infty, and an equilibrium…

Statistical Mechanics · Physics 2015-06-24 Yves Elskens

We analyze the probability density function (PDF) of waiting times between financial loss exceedances. The empirical PDFs are fitted with the self-excited Hawkes conditional Poisson process with a long power law memory kernel. The Hawkes…

Statistical Finance · Quantitative Finance 2017-05-24 Maciej Jagielski , Ryszard Kutner , Didier Sornette

In this article, we quantify the functional convergence of the rescaled random walk with heavy tails to a stable process.This generalizes the Generalized Central Limit Theorem for stable random variables infinite dimension. We show that…

Probability · Mathematics 2026-04-02 Lorick Huang , Laurent Decreusefond , Laure Coutin

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

We model the arrival of mid-price changes in the E-Mini S&P futures contract as a self-exciting Hawkes process. Using several estimation methods, we find that the Hawkes kernel is power-law with a decay exponent close to -1.15 at short…

Statistical Finance · Quantitative Finance 2015-06-12 Stephen J. Hardiman , Nicolas Bercot , Jean-Philippe Bouchaud

Branching processes in a random environment are natural generalisations of Galton-Watson processes. In this paper we analyse the asymptotic decay of the survival probability for a sequence of slightly supercritical branching processes in an…

Probability · Mathematics 2024-12-23 Florin Boenkost , Götz Kersting

In the last decade Hawkes processes have received much attention as models for functional connectivity in neural spiking networks and other dynamical systems with a cascade behavior. In this paper we establish a renewal approach for…

Probability · Mathematics 2019-06-11 Mads Bonde Raad

Point processes are widely used statistical models for continuous-time discrete event data, such as medical records, crime reports, and social network interactions, to capture the influence of historical events on future occurrences. In…

Machine Learning · Statistics 2026-01-13 Xiuyuan Cheng , Tingnan Gong , Yao Xie

For a subcritical Galton-Watson process $(\zeta_n)$, it is well known that under an $X \log X$ condition, the quotient $P(\zeta_n > 0)/ E\zeta_n$ has a finite positive limit. There is an analogous result for a (one-dimensional)…

Probability · Mathematics 2007-05-23 Jean Bertoin , Alain Rouault

Starting from a simple animal-biology example, a general, somewhat counter-intuitive property of diffusion random walks is presented. It is shown that for any (non-homogeneous) purely diffusing system, under any isotropic uniform incidence,…

Statistical Mechanics · Physics 2019-02-20 Stephane Blanco , Fournier Richard

In this paper the asymptotic behaviour of a critical 2-type Galton-Watson process with immigration is described when its offspring mean matrix is reducible, in other words, when the process is decomposable. It is proved that, under second…

Probability · Mathematics 2023-11-21 Matyas Barczy , Dániel Bezdány , Gyula Pap

Motivated by the phenomenon of duality for interacting particle systems we introduce two classes of Pfaffian kernels describing a number of Pfaffian point processes in the `bulk' and at the `edge'. Using the probabilistic method due to Mark…

Probability · Mathematics 2023-05-04 Will FitzGerald , Roger Tribe , Oleg Zaboronski

We study the behavior of the random walk in a continuum independent long-range percolation model, in which two given vertices $x$ and $y$ are connected with probability that asymptotically behaves like $|x-y|^{-\alpha}$ with $\alpha>d$,…

Probability · Mathematics 2022-09-30 Ercan Sönmez , Arnaud Rousselle

We make and generalize the observation that summing of probability amplitudes of a discrete-time quantum walk over partitions of the walking graph consistent with the step operator results in a unitary evolution on the reduced graph which…

Quantum Physics · Physics 2020-04-06 Václav Potoček

In this paper, we derive an explicit upper bound for the Wasserstein distance between a functional of point processes and a Gaussian distribution. Using Stein's method in conjunction with Malliavin's calculus and the Poisson embedding…

Probability · Mathematics 2025-06-09 Laure Coutin , Benjamin Massat , Anthony Réveillac

A critical branching process $\left\{ Z_{k},k=0,1,2,...\right\} $ in a random environment is considered. A conditional functional limit theorem for the properly scaled process $\left\{ \log Z_{pu},0\leq u<\infty \right\} $ is established…

Probability · Mathematics 2016-03-11 Vladimir Vatutin , Elena Dyakonova

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