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We first state a special type of It\^o formula involving stochastic integrals of both standard and fractional Brownian motions. Then we use Doss-Sussman transformation to establish the link between backward doubly stochastic differential…

Probability · Mathematics 2011-03-18 Shuai Jing

We study the stochastic motion of particles driven by long-range correlated fractional Gaussian noise in a superharmonic external potential of the form $U(x)\propto x^{2n}$ ($n\in\mathbb{N}$). When the noise is considered to be external,…

Statistical Mechanics · Physics 2021-06-17 Tobias Guggenberger , Aleksei Chechkin , Ralf Metzler

This article investigates several properties related to densities of solutions X to differential equations driven by a fractional Brownian motion with Hurst parameter H>1/4. We first determine conditions for strict positivity of the density…

Probability · Mathematics 2014-01-16 Fabrice Baudoin , Eulalia Nualart , Cheng Ouyang , Samy Tindel

In this paper, we generalize to Gaussian Volterra processes the existence and uniqueness of solutions for a class of non linear backward stochastic differential equations (BSDE) and we establish the relation between the non linear BSDE and…

Probability · Mathematics 2020-05-15 Habiba Knani

In this work, we prove a version of H\"{o}rmander's theorem for a stochastic evolution equation driven by a trace-class fractional Brownian motion with Hurst exponent $\frac{1}{2} < H < 1$ and an analytic semigroup on a given separable…

Probability · Mathematics 2020-03-19 Jorge A. de Nascimento , Alberto Ohashi

This paper discusses the fractional diffusion equation forced by a tempered fractional Gaussian noise. The fractional diffusion equation governs the probability density function of the subordinated killed Brownian motion. The tempered…

Numerical Analysis · Mathematics 2020-07-14 Xing Liu , Weihua Deng

We consider stochastic differential equations of the form $dY_t=V(Y_t)\,dX_t+V_0(Y_t)\,dt$ driven by a multi-dimensional Gaussian process. Under the assumption that the vector fields $V_0$ and $V=(V_1,\ldots,V_d)$ satisfy H\"{o}rmander's…

Probability · Mathematics 2015-01-21 Thomas Cass , Martin Hairer , Christian Litterer , Samy Tindel

We investigate properties of the (conditional) law of the solution to SDEs driven by fractional Brownian noise with a singular, possibly distributional, drift. Our results on the law are twofold: i) we quantify the spatial regularity of the…

Probability · Mathematics 2025-06-16 Lukas Anzeletti , Lucio Galeati , Alexandre Richard , Etienne Tanré

This paper investigates the probability distribution of solutions to McKean--Vlasov stochastic differential equations driven by fractional Brownian motion with Hurst parameter H>1/2. Our main contribution is the derivation of the associated…

Probability · Mathematics 2026-01-12 Saloua Labed , Nacira Agram , Bernt Oksendal

The Malliavin differentiability of a SDE plays a crucial role in the study of density smoothness and ergodicity among others. For Gaussian driven SDEs the differentiability property is now well established. In this paper, we consider the…

Probability · Mathematics 2023-05-18 Jorge A. León , Yanghui Liu , Samy Tindel

We study some functional inequalities satisfied by the distribution of the solution of a stochastic differential equation driven by fractional Brownian motions. Such functional inequalities are obtained through new integration by parts…

Probability · Mathematics 2011-02-23 Fabrice Baudoin , Cheng Ouyang

In this paper, we study the existence of densities (with respect to the Lebesgue measure) for marginal laws of the solution $(Y,Z)$ to a quadratic growth BSDE. Using the (by now) well-established connection between these equations and their…

Probability · Mathematics 2015-01-27 Thibaut Mastrolia , Dylan Possamaï , Anthony Réveillac

Probabilistic ordinary differential equation (ODE) solvers have been introduced over the past decade as uncertainty-aware numerical integrators. They typically proceed by assuming a functional prior to the ODE solution, which is then…

Numerical Analysis · Mathematics 2025-03-25 Yvann Le Fay , Simo Särkkä , Adrien Corenflos

Fractional Brownian motion is a Gaussian stochastic process with stationary, long-time correlated increments and is frequently used to model anomalous diffusion processes. We study numerically fractional Brownian motion confined to a finite…

Statistical Mechanics · Physics 2019-03-22 T. Guggenberger , G. Pagnini , T. Vojta , R. Metzler

We study the existence of a unique solution to semilinear fractional backward doubly stochastic differential equation driven by a Brownian motion and a fractional Brownian motion with Hurst parameter less than 1/2. Here the stochastic…

Probability · Mathematics 2010-05-13 Shuai Jing , Jorge León

We survey existing results concerning the study in small times of the density of the solution of a rough differential equation driven by fractional Brownian motions. We also slightly improve existing results and discuss some possible…

Probability · Mathematics 2014-03-05 Fabrice Baudoin , Cheng Ouyang

In this paper, we study the well-posedness of multi-dimensional backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs) with diagonal generators, the $z$ parts of whose $l$-th components only depend on the…

Probability · Mathematics 2020-02-18 Guomin Liu

This paper is concerned with the backward stochastic differential equations whose generator is a weighted fractional Brownian field: $Y_t=\xi+\int_t^T Y_s W (ds,B_s) -\int_t^T Z_sdB_s$, $0\le t\le T$, where $W$ is a $(d+1)$-parameter…

Probability · Mathematics 2022-08-02 Yaozhong Hu , Juan Li , Chao Mi

This article deals with the numerical resolution of backward stochastic differential equations. Firstly, we consider a rather general case where the filtration is generated by a Brownian motion and a Poisson random measure. We provide a…

Probability · Mathematics 2008-12-18 Emmanuel Gobet , Jean-Philippe Lemor

In this note, we investigate the density of the exponential functional of the fractional Brownian motion. Based on the techniques of Malliavin's calculus, we provide a log-normal upper bound for the density.

Probability · Mathematics 2021-09-23 Nguyen Tien Dung , Nguyen Thu Hang , Pham Thi Phuong Thuy