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In this paper, by using a Taylor development type formula, we show how it is possible to associate differential operators with stochastic differential equations driven by a fractional Brownian motion. As an application, we deduce that…

Probability · Mathematics 2007-05-23 Fabrice Baudoin , Laure Coutin

In this paper we consider stochastic differential equations with non-negativity constraints, driven by a fractional Brownian motion with Hurst parameter $H>\1/2$. We first study an ordinary integral equation where the integral is defined in…

Probability · Mathematics 2012-03-14 Marco Ferrante , Carles Rovira

This work aims to estimate the drift and diffusion functions in stochastic differential equations (SDEs) driven by a particular class of L\'evy processes with finite jump intensity, using neural networks. We propose a framework that…

Machine Learning · Statistics 2025-07-10 Jose-Hermenegildo Ramirez-Gonzalez , Ying Sun

The application of Stochastic Differential Equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we…

Machine Learning · Statistics 2017-08-09 Constantino A. García , Abraham Otero , Paulo Félix , Jesús Presedo , David G. Márquez

In this paper, we study linear backward stochastic differential equations driven by a class of centered Gaussian non-martingales, including fractional Brownian motion with Hurst parameter $H\in (0,1)\setminus \{\frac12\}$. We show that, for…

Probability · Mathematics 2016-01-20 Christian Bender , Lauri Viitasaari

We study a process satisfying a one-dimensional stochastic differential equation driven by fractional Brownian motion with Hurst index $H>1/2$, and consider the weighted power variation based on the second order differences of the process.…

Probability · Mathematics 2024-07-04 Hayate Yamagishi

We study a least square-type estimator for an unknown parameter in the drift coefficient of a stochastic differential equation with additive fractional noise of Hurst parameter H>1/2. The estimator is based on discrete time observations of…

Probability · Mathematics 2011-11-10 Andreas Neuenkirch , Samy Tindel

In this article, we present a general methodology for control problems driven by the Brownian motion filtration including non-Markovian and non-semimartingale state processes controlled by mutually singular measures. The main result of this…

Probability · Mathematics 2018-01-19 Dorival Leão , Alberto Ohashi , Francys Souza

This article deals with the numerical resolution of Markovian backward stochastic differential equations (BSDEs) with drivers of quadratic growth with respect to $z$ and bounded terminal conditions. We first show some bound estimates on the…

Probability · Mathematics 2012-01-10 Adrien Richou

We study nonparametric density estimation in non-stationary drift settings. Given a sequence of independent samples taken from a distribution that gradually changes in time, the goal is to compute the best estimate for the current…

Machine Learning · Computer Science 2023-10-31 Alessio Mazzetto , Eli Upfal

We consider statistics for stochastic evolution equations in Hilbert space with emphasis on stochastic partial differential equations (SPDEs). We observe a solution process under additional measurement errors and want to estimate a real or…

Statistics Theory · Mathematics 2025-05-21 Gregor Pasemann , Markus Reiß

In this paper, we consider the problem of estimating the drift parameter of solution to the stochastic differential equation driven by a fractional Brownian motion with Hurst parameter less than $1/2$ under complete observation. We derive a…

Statistics Theory · Mathematics 2018-07-11 Kohei Chiba

This paper is devoted to a system of stochastic partial differential equations (SPDEs) that have a slow component driven by fractional Brownian motion (fBm) with the Hurst parameter $H >1/2$ and a fast component driven by fast-varying…

Probability · Mathematics 2021-11-12 Bin Pei , Yuzuru Inahama , Yong Xu

The fractional Brownian motion can be considered as a Gaussian field indexed by $(t,H)\in {\mathbb{R}_{+}\times (0,1)}$, where $H$ is the Hurst parameter. On compact time intervals, it is known to be almost surely jointly H\"older…

Probability · Mathematics 2025-02-06 El Mehdi Haress , Alexandre Richard

We design numerical schemes for a class of slow-fast systems of stochastic differential equations, where the fast component is an Ornstein-Uhlenbeck process and the slow component is driven by a fractional Brownian motion with Hurst index…

Probability · Mathematics 2021-04-30 Charles-Edouard Bréhier

In this study, we develop a new theory of estimating Hurst parame- ter using conic multivariate adaptive regression splines (CMARS) method. We concentrate on the strong solution of stochastic differentional equations (SDEs) driven by…

This paper investigates a non-autonomous slow-fast system, which is generalized by stochastic differential equations (SDEs) with locally Lipschitz coefficients, subjected to standard Brownian motion (Bm) and fractional Brownian motion (fBm)…

Probability · Mathematics 2020-12-21 Ruifang Wang , Yong Xu , Hongge Yue

We study the long-time behaviour of solutions to a class of $d$-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H \in (0,1)$. The drift consists of a dissipative Lipschitz term and a…

Probability · Mathematics 2025-12-23 Konstantinos Dareiotis , El Mehdi Haress , Khoa Lê

We show a concise extension of the monotone stability approach to backward stochastic differential equations (BSDEs) that are jointly driven by a Brownian motion and a random measure for jumps, which could be of infinite activity with a…

Probability · Mathematics 2019-11-21 Dirk Becherer , Martin Büttner , Klebert Kentia

In this paper, we establish the strong well-posedness of SDEs with merely integrable time-dependent drifts driven by fractional Brownian motions with Hurst parameter H<1/2. Our result holds over the entire subcritical regime and can be…

Probability · Mathematics 2026-02-26 Jiazhen Gu , Qian Yu