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We study functional limit theorems for linear type processes with short memory under the assumption that the innovations are dependent identically distributed random variables with infinite variance and in the domain of attraction of stable…

Probability · Mathematics 2010-05-20 Marta Tyran-Kaminska

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

Hawkes Process has been used to model Limit Order Book (LOB) dynamics in several ways in the literature however the focus has been limited to capturing the inter-event times while the order size is usually assumed to be constant. We propose…

Trading and Market Microstructure · Quantitative Finance 2024-08-15 Konark Jain , Nick Firoozye , Jonathan Kochems , Philip Treleaven

We establish central limit theorems for a large class of supercritical branching Markov processes in infinite dimension with spatially dependent and non-necessarily local branching mechanisms. This result relies on a fourth moment…

Probability · Mathematics 2025-01-31 Bertrand Cloez , Nicolás Zalduendo

We present a careful analysis of possible issues on the application of the self-excited Hawkes process to high-frequency financial data. We carefully analyze a set of effects leading to significant biases in the estimation of the…

Statistical Finance · Quantitative Finance 2014-07-04 Vladimir Filimonov , Didier Sornette

We develop a quasi-likelihood analysis procedure for a general class of multivariate marked point processes. As a by-product of the general method, we establish under stability and ergodicity conditions the local asymptotic normality of the…

Statistics Theory · Mathematics 2021-08-06 Simon Clinet

We prove a central limit theorem for a sequence of random variables whose means are ambiguous and vary in an unstructured way. Their joint distribution is described by a set of measures. The limit is (not the normal distribution and is)…

Probability · Mathematics 2020-07-01 Zengjing Chen , Larry G. Epstein

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

We establish central limit theorems for general functionals on binomial point processes and their Poissonized version. As an application, a central limit theorem for Betti numbers of random geometric complexes in the thermodynamic regime is…

Probability · Mathematics 2018-04-10 Khanh Duy Trinh

We have shown recently that a Markov process conditioned on rare events involving time-integrated random variables can be described in the long-time limit by an effective Markov process, called the driven process, which is given…

Statistical Mechanics · Physics 2015-12-17 Raphael Chetrite , Hugo Touchette

Let $(W_n(\theta))_{n\in\mathbb N_0}$ be the Biggins martingale associated with a supercritical branching random walk and denote by $W_\infty(\theta)$ its limit. Assuming essentially that the martingale $(W_n(2\theta))_{n\in\mathbb N_0}$ is…

Probability · Mathematics 2016-01-14 Alexander Iksanov , Zakhar Kabluchko

Consider a supercritical Crump--Mode--Jagers process $(\mathcal Z_t^{\varphi})_{t \geq 0}$ counted with a random characteristic $\varphi$. Nerman's celebrated law of large numbers [Z. Wahrsch. Verw. Gebiete 57, 365--395, 1981] states that,…

Probability · Mathematics 2024-03-13 Alexander Iksanov , Konrad Kolesko , Matthias Meiners

We characterize the convergence in distribution to a standard normal law for a sequence of multiple stochastic integrals of a fixed order with variance converging to 1. Some applications are given, in particular to study the limiting…

Probability · Mathematics 2007-05-23 David Nualart , Giovanni Peccati

In this paper we consider the statistics of repeated measurements on the output of a quantum Markov chain. We establish a large deviations result analogous to Sanov's theorem for the empirical measure associated to finite sequences of…

Quantum Physics · Physics 2015-06-22 Merlijn van Horssen , Madalin Guta

We study inhomogeneous random graphs with a finite type space. For a natural generalization of the model as a dynamic network-valued process, the paper establishes the following results: (a) Functional central limit theorems for the…

Probability · Mathematics 2025-01-22 Shankar Bhamidi , Amarjit Budhiraja , Akshay Sakanaveeti

We study a multivariate Hawkes process as a model for time-continuous relational event networks. The model does not assume the network to be known, it includes covariates, and it allows for both common drivers, parameters common to all the…

Statistics Theory · Mathematics 2025-04-08 Alexander Kreiss , Enno Mammen , Wolfgang Polonik

We introduce a model for limit order book of a certain security with two main features: First, both the limit orders and market orders for the given asset are allowed to appear and interact with each other. Second, the high frequency…

Pricing of Securities · Quantitative Finance 2024-12-24 Yun Chen-Shue , Yukun Li , Jiongmin Yong

In this paper we consider multivariate Hawkes processes with baseline hazard and kernel functions that depend on time. This defines a class of locally stationary processes. We discuss estimation of the time-dependent baseline hazard and…

Statistics Theory · Mathematics 2017-07-17 Enno Mammen

Linear multivariate Hawkes processes (MHP) are a fundamental class of point processes with self-excitation. When estimating parameters for these processes, a difficulty is that the two main error functionals, the log-likelihood and the…

Methodology · Statistics 2021-11-23 Álvaro Cartea , Samuel N. Cohen , Saad Labyad

Oscillatory systems of interacting Hawkes processes with Erlang memory kernels were introduced in Ditlevsen (2017). They are piecewise deterministic Markov processes (PDMP) and can be approximated by a stochastic diffusion. First, a strong…

Numerical Analysis · Mathematics 2020-03-25 Julien Chevallier , Anna Melnykova , Irene Tubikanec