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We demonstrate that two Ornstein--Uhlenbeck processes, that is, solutions to certain stochastic differential equations that are driven by a L\'evy process L have equivalent laws as long as the eigenvalues of the covariance operator…

Probability · Mathematics 2019-05-14 Grzegorz Bartosz , Tomasz Kania

For an arbitrary L\'evy process $X$ which is not a compound Poisson process, we are interested in its occupation times. We use a quite novel and useful approach to derive formulas for the Laplace transform of the joint distribution of $X$…

Probability · Mathematics 2016-04-04 Lan Wu , Jiang Zhou , Shuang Yu

Markovian diffusion processes yield a system of conservation laws which couple various conditional expectation values (local moments). Solutions of that closed system of deterministic partial differential equations stand for a regular…

Statistical Mechanics · Physics 2007-05-23 P. Garbaczewski

Ito's construction of Markovian solutions to stochastic equations driven by a L\'evy noise is extended to nonlinear distribution dependent integrands aiming at the effective construction of linear and nonlinear Markov semigroups and the…

Probability · Mathematics 2022-05-03 Vassili N. Kolokoltsov

We propose a novel class of tempo-spatial Ornstein-Uhlenbeck processes as solutions to L\'evy-driven Volterra equations with additive noise and multiplicative drift. After formulating conditions for the existence and uniqueness of…

Probability · Mathematics 2019-03-26 Viet Son Pham , Carsten Chong

In this work, we study the class of stochastic process that generalizes the Ornstein-Uhlenbeck processes, hereafter called by \emph{Generalized Ornstein-Uhlenbeck Type Process} and denoted by GOU type process. We consider them driven by the…

Statistics Theory · Mathematics 2021-08-17 J. Stein , S. R. C. Lopes , A. V. Medino

Dilative stability generalizes the property of selfsimilarity for infinitely divisible stochastic processes by introducing an additional scaling in the convolution exponent. Inspired by results of Igl\'oi, we will show how dilatively stable…

Probability · Mathematics 2018-06-15 Thorsten Bhatti , Peter Kern

We study a class of stationary Markov processes with marginal distributions identifiable by moments such that every conditional moment of degree say $m$ is a polynomial of degree at most $m\;\text{.}\;$ We show that then under some…

Probability · Mathematics 2017-05-19 Paweł J. Szabłowski

In this article, the problem of semi-parametric inference on the parameters of a multidimensional L\'{e}vy process $L_t$ with independent components based on the low-frequency observations of the corresponding time-changed L\'{e}vy process…

Methodology · Statistics 2012-01-31 Denis Belomestny

In this paper we study general nonlinear stochastic differential equations, where the usual Brownian motion is replaced by a L\'evy process. We also suppose that the coefficient multiplying the increments of this process is merely Lipschitz…

Probability · Mathematics 2007-07-19 Benjamin Jourdain , Sylvie Méléard , Wojbor Woyczynski

The Ornstein-Uhlenbeck process is interpreted as Brownian motion in a harmonic potential. This Gaussian Markov process has a bounded variance and admits a stationary probability distribution, in contrast to the standard Brownian motion. It…

Statistical Mechanics · Physics 2023-06-07 Pece Trajanovski , Petar Jolakoski , Kiril Zelenkovski , Alexander Iomin , Ljupco Kocarev , Trifce Sandev

We present a satisfactory definition of the important class of L\'evy processes indexed by a general collection of sets. We use a new definition for increment stationarity of set-indexed processes to obtain different characterizations of…

Probability · Mathematics 2012-01-25 Erick Herbin , Ely Merzbach

We establish sufficient conditions for the existence, and derive explicit formulas for the $\kappa$'th moments, $\kappa \geq 1$, of Markov modulated generalized Ornstein-Uhlenbeck processes as well as their stationary distributions. In…

Probability · Mathematics 2024-05-15 Anita Behme , Paolo Di Tella , Apostolos Sideris

The goal of this paper is to derive a formula for the finite dimensional joint characteristic function (the Fourier transform of the finite dimensional distribution) of the coupled process ${(W_{t},L_{t}^{A}):t\in \lbrack 0,\infty)}$, where…

Probability · Mathematics 2012-06-07 Xi Geng , Zhongmin Qian

We study a one-dimensional kinetic stochastic model driven by a L{\'e}vy process with a non-linear time-inhomogeneous drift. More precisely, the process $(V,X)$ is considered, where $X$ is the position of the particle and its velocity $V$…

Probability · Mathematics 2022-04-25 Mihai Gradinaru , Emeline Luirard

By using the existing sharp estimates of density function for rotationally invariant symmetric $\alpha$-stable L\'{e}vy processes and rotationally invariant symmetric truncated $\alpha$-stable L\'{e}vy processes, we obtain that Harnack…

Probability · Mathematics 2011-05-17 Jian Wang

We develop a stochastic integration theory for predictable integrands with respect to a L\'evy basis. Our approach is based on decoupling inequalities for tangent sequences and reduces the construction of the stochastic integral essentially…

Probability · Mathematics 2026-05-18 Markus Riedle

Using Riemann-Stieltjes methods for integrators of bounded $p$-variation we define a pathwise integral driven by a fractional L\'{e}vy process (FLP). To explicitly solve general fractional stochastic differential equations (SDEs) we…

Statistics Theory · Mathematics 2011-02-10 Holger Fink , Claudia Klüppelberg

This paper continues the research project launched in [Constr. Approx. (2025) https://doi.org/10.1007/s00365-023-09675-9] and aimed at studying time-inhomogeneous one-dimensional branching processes (mainly on a continuous but also on a…

Probability · Mathematics 2025-12-16 Pavel Gumenyuk , Takahiro Hasebe , José-Luis Pérez

In this work, we introduce a theory of stochastic integration with respect to symmetric $\alpha$-stable cylindrical L\'evy processes. Since $\alpha$-stable cylindrical L\'evy processes do not enjoy a semi-martingale decomposition, our…

Probability · Mathematics 2022-11-21 Gergely Bodó , Markus Riedle