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In this article, we study the numerical approximation of stochastic differential equations driven by a multidimensional fractional Brownian motion (fBm) with Hurst parameter greater than 1/3. We introduce an implementable scheme for these…

Probability · Mathematics 2015-05-18 Aurélien Deya , Andreas Neuenkirch , Samy Tindel

We consider a problem of parameter estimation for the state space model described by linear stochastic differential equations. We assume that an unobservable Ornstein-Uhlenbeck process drives another observable process by the linear…

Statistics Theory · Mathematics 2022-03-25 Masahiro Kurisaki

We introduce the elliptical Ornstein-Uhlenbeck (OU) process, which is a generalisation of the well-known univariate OU process to bivariate time series. This process maps out elliptical stochastic oscillations over time in the complex…

Methodology · Statistics 2021-12-08 Adam M. Sykulski , Sofia C. Olhede , Hanna M. Sykulska-Lawrence

We consider the problem of static Bayesian inference for partially observed Levy-process models. We develop a methodology which allows one to infer static parameters and some states of the process, without a bias from the…

Computation · Statistics 2022-04-01 Hamza Ruzayqat , Ajay Jasra

By employing a path integral formulation, we obtain the entropy production rate for a system of active Ornstein-Uhlenbeck particles (AOUP) both in the presence and in the absence of thermal noise. The present treatment clarifies some…

Statistical Mechanics · Physics 2019-09-04 Lorenzo Caprini , Umberto Marini Bettolo Marconi , Andrea Puglisi , Angelo Vulpiani

Let $\theta>0$. We consider a one-dimensional fractional Ornstein-Uhlenbeck process defined as $dX_t= -\theta\ X_t dt+dB_t,\quad t\geq0,$ where $B$ is a fractional Brownian motion of Hurst parameter $H\in(1/2,1)$. We are interested in the…

Probability · Mathematics 2013-07-17 Khalifa Es-Sebaiy

We examine a mean-reverting Ornstein-Uhlenbeck process that perturbs an unknown Lipschitz-continuous drift and aim to estimate the drift's value at a predetermined time horizon by sampling the path of the process. Due to the time varying…

Statistics Theory · Mathematics 2024-05-20 Enrico Bernardi , Alberto Lanconelli , Christopher S. A. Lauria , Berk Tan Perçin

The paper is devoted to three-parametric self-similar Gaussian Volterra processes that generalize fractional Brownian motion. We study the asymptotic growth of such processes and the properties of long- and short-range dependence. Then we…

Statistics Theory · Mathematics 2023-02-08 Yuliya Mishura , Kostiantyn Ralchenko , Sergiy Shklyar

Rough path analysis can be developed using the concept of controlled paths, and with respect to a topology in which L\'evy's area plays a role. For vectors of irregular paths we investigate the relationship between the property of being…

Probability · Mathematics 2017-04-26 Peter Imkeller , David J. Prömel

We construct the "expected signature matching" estimator for differential equations driven by rough paths and we prove its consistency and asymptotic normality. We use it to estimate parameters of a diffusion and a fractional diffusions,…

Probability · Mathematics 2011-12-16 Anastasia Papavasiliou , Christophe Ladroue

The aim of this paper is twofold. First, it offers a novel formula to calculate the inner product of the bounded variation function in the Hilbert space $\mathcal{H}$ associated with the fractional Brownian motion with Hurst parameter $H\in…

Probability · Mathematics 2022-10-04 Yong Chen , Xiangmeng Gu

Consider a multivariate L\'evy-driven Ornstein-Uhlenbeck process where the stationary distribution or background driving L\'evy process is from a parametric family. We derive the likelihood function assuming that the innovation term is…

Statistics Theory · Mathematics 2021-09-01 Kevin W. Lu

Starting from the construction of a geometric rough path associated with a fractional Brownian motion with Hurst parameter $H\in]{1/4}, {1/2}[$ given by Coutin and Qian (2002), we prove a large deviation principle in the space of geometric…

Probability · Mathematics 2007-05-23 Annie Millet , Marta Sanz-Solé

In this paper, we investigate a deep learning method for predicting path-dependent processes based on discretely observed historical information. This method is implemented by considering the prediction as a nonparametric regression and…

Machine Learning · Statistics 2024-08-20 Xudong Zheng , Yuecai Han

Malliavin Calculus is about Sobolev-type regularity of functionals on Wiener space, the main example being the Ito map obtained by solving stochastic differential equations. Rough path analysis is about strong regularity of solution to…

Probability · Mathematics 2007-11-12 Thomas Cass , Peter Friz , Nicolas Victoir

The aim of this paper is to develop estimation and inference methods for the drift parameters of multivariate L\'evy-driven continuous-time autoregressive processes of order $p\in\mathbb{N}$. Starting from a continuous-time observation of…

Methodology · Statistics 2023-07-26 Lorenzo Lucchese , Mikko S. Pakkanen , Almut E. D. Veraart

We introduce a canonical way of performing the joint lift of a Brownian motion $W$ and a low-regularity adapted stochastic rough path $\mathbf{X}$, extending [Diehl, Oberhauser and Riedel (2015). A L\'evy area between Brownian motion and…

Mathematical Finance · Quantitative Finance 2026-03-10 Ofelia Bonesini , Emilio Ferrucci , Ioannis Gasteratos , Antoine Jacquier

We consider a geometric rough path associated with a fractional Brownian motion with Hurst parameter $H\in]{1/4}, {1/2}[$. We give an approximation result in a modulus type distance, up to the second order, by means of a sequence of rough…

Probability · Mathematics 2009-01-20 Annie Millet , Marta Sanz-Solé

This article is concerned with stochastic differential equations driven by a $d$ dimensional fractional Brownian motion with Hurst parameter $H>1/4$, understood in the rough paths sense. Whenever the coefficients of the equation satisfy a…

Probability · Mathematics 2019-07-02 Xi Geng , Cheng Ouyang , Samy Tindel

We are interested in the law of the first passage time of an Ornstein-Uhlenbeck process to time-varying thresholds. We show that this problem is connected to the laws of the first passage time of the process to members of a two-parameter…

Probability · Mathematics 2024-03-26 Aria Ahari , Larbi Alili , Massimiliano Tamborrino