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We study the stationary fluctuations of independent run-and-tumble particles. We prove that the joint densities of particles with given internal state converges to an infinite dimensional Ornstein-Uhlenbeck process. We also consider an…

Probability · Mathematics 2024-03-13 Frank Redig , Hidde van Wiechen

In this paper, we build on the techniques developed in Albrecher et al. (2013), to generate initial-boundary value problems for ruin probabilities of surplus-dependent premium risk processes, under a renewal case scenario, Erlang (2) claim…

Probability · Mathematics 2021-01-12 Corina Constantinescu , Zbigniew Palmowski , Jing Wang

We first study the drift parameter estimation of the fractional Ornstein-Uhlenbeck process (fOU) with periodic mean for every $\frac{1}{2}<H<1$. More precisely, we extend the consistency proved in \cite{DFW} for $\frac{1}{2}<H<\frac{3}{4}$…

Probability · Mathematics 2016-09-28 Salwa Bajja , Khalifa Es-Sebaiy , Lauri Viitasaari

In this article we study the asymptotic behaviour of the realized quadratic variation of a process $\int_{0}^{t}u_{s}dY_{s}^{(1)}$% , where $u$ is a $\beta$-H\"older continuous process with $\beta > 1-H$ and…

Probability · Mathematics 2018-02-28 Salwa Bajja , Khalifa Es-Sebaiy , Lauri Viitasaari

We obtain a Berry-Esseen type bound for the distribution of the maximum likelihood estimator of the drift parameter for fractional Ornstein-uhlenbeck type process driven by sub-fractional Brownian motion.

Probability · Mathematics 2019-01-21 B. L. S. Prakasa Rao

The survival probability for a periodic non-autonomous Ornstein-Uhlenbeck process is calculated analytically using two different methods. The first uses an asymptotic approach. We treat the associated Kolmogorov Backward Equation with an…

Statistical Mechanics · Physics 2025-01-20 L. T. Giorgini , W. Moon , J. S. Wettlaufer

For the Ornstein-Uhlenbeck process, the asymptotic behavior of the maximum likelihood estimator of the drift parameter is totally different in the stable, unstable, and explosive cases. Notwithstanding of this trichotomy, we investigate…

Probability · Mathematics 2011-11-28 Bernard Bercu , Laure Coutin , Nicolas Savy

In this paper we look at ergodic BSDEs in the case where the forward dynamics are given by the solution to a non-autonomous (time-periodic coefficients) Ornstein-Uhlenbeck SDE with L\'evy noise, taking values in a separable Hilbert space.…

Probability · Mathematics 2015-11-11 Samuel N. Cohen , Victor Fedyashov

We consider a fractional Ornstein-Uhlenbeck process involving a stochastic forcing term in the drift, as a solution of a linear stochastic differential equation driven by a fractional Brownian motion. For such process we specify mean and…

Probability · Mathematics 2020-09-25 Giacomo Ascione , Yuliya Mishura , Enrica Pirozzi

We consider a $d$-dimensional stochastic differential equation (SDE) of the form $d U_t = b(U_t) dt + \sigma\,d Z_t$, let $X_t$ be the solution if the driving noise $Z_t$ is a $d$-dimensional rotationally symmetric $\alpha$-stable process…

Probability · Mathematics 2025-11-25 Changsong Deng , Xiang Li , Rene L. Schilling , Lihu Xu

We investigate large deviation properties of the maximum likelihood drift parameter estimator for Ornstein--Uhlenbeck process driven by mixed fractional Brownian motion.

Probability · Mathematics 2016-07-14 Dmytro Marushkevych

To investigate the complex dynamics of a biological neuron that is subject to small random perturbations we can use stochastic neuron models. While many techniques have already been developed to study properties of such models, especially…

Neurons and Cognition · Quantitative Biology 2017-07-18 Jan H. Kirchner

Consider the linear stochastic differential equation (SDE) on $\mathbb{R}^n$: \[\mathrm {d}{X}_t=AX_t\,\mathrm{d}t+B\,\mathrm{d}L_t,\] where $A$ is a real $n\times n$ matrix, $B$ is a real $n\times d$ real matrix and $L_t$ is a L\'{e}vy…

Probability · Mathematics 2012-01-06 Feng-Yu Wang

We consider the problem of simultaneously approximating the conditional distribution of market prices and their log returns with a single machine learning model. We show that an instance of the GDN model of Kratsios and Papon (2022) solves…

Computational Finance · Quantitative Finance 2023-02-21 Anastasis Kratsios , Cody Hyndman

We consider a classical risk process with arrival of claims following a non-stationary Hawkes process. We study the asymptotic regime when the premium rate and the baseline intensity of the claims arrival process are large, and claim size…

Risk Management · Quantitative Finance 2019-08-22 Zailei Cheng , Youngsoo Seol

Let x(s), s in R^d be a Gaussian self-similar random process of index H. We consider the problem of log-asymptotics for the probability p(T) that x(s), x(0)=0 does not exceed a fixed level in a star-shaped expanding domain TxG as T>>1. We…

Probability · Mathematics 2007-05-23 G. Molchan

Modern methods of generative modelling and unpaired data translation based on Schr\"odinger bridges and stochastic optimal control theory aim to transform an initial density to a target one in an optimal way. In the present paper, we assume…

Machine Learning · Computer Science 2026-03-24 Nikita Puchkin , Denis Suchkov , Alexey Naumov , Denis Belomestny

For certain materials science scenarios arising in rubber technology, one-dimensional moving boundary problems (MBPs) with kinetic boundary conditions are capable of unveiling the large-time behavior of the diffusants penetration front,…

Numerical Analysis · Mathematics 2023-12-04 Surendra Nepal , Magnus Ogren , Yosief Wondmagegne , Adrian Muntean

The indefinite integral of the homogenized Ornstein-Uhlenbeck process is a well-known model for physical Brownian motion, modelling the behaviour of an object subject to random impulses [L. S. Ornstein, G. E. Uhlenbeck: On the theory of…

Probability · Mathematics 2013-02-12 Peter Friz , Paul Gassiat , Terry Lyons

We study a new technique for the asymptotic analysis of heavy-tailed systems conditioned on large deviations events. We illustrate our approach in the context of ruin events of multidimensional regularly varying random walks. Our approach…

Statistics Theory · Mathematics 2014-03-10 Jose Blanchet , Jingchen Liu