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We establish Talagrand's $T_1$ and $T_2$ inequalities for the law of the solution of a stochastic differential equation driven by a fractional Brownian motion with Hurst parameter $H>1/2$. We use the $L^2$ metric and the uniform metric on…

Statistics Theory · Mathematics 2012-03-01 Bruno Saussereau

We consider stochastic differential equation $$ d X_t=b(X_t) dt +d W_t^H, $$ where the drift $b$ is either a measure or an integrable function, and $W^H$ is a $d$-dimensional fractional Brownian motion with Hurst parameter $H\in(0,1)$,…

Probability · Mathematics 2025-10-22 Oleg Butkovsky , Khoa Lê , Leonid Mytnik

We prove existence and uniqueness of the solution for a class of mixed fractional stochastic differential equations with discontinuous drift driven by both standard and fractional Brownian motion. Additionally, we establish a generalized…

Probability · Mathematics 2024-04-05 Ercan Sönmez

We establish the rate of convergence in the $L^1$-norm for equidistant approximations of stochastic integrals with discontinuous integrands driven by multifractional Brownian motion. Our findings extend the known results for the case when…

Probability · Mathematics 2024-08-06 Kostiantyn Ralchenko , Foad Shokrollahi , Tommi Sottinen

We study a class of semi-implicit Taylor-type numerical methods that are easy to implement and designed to solve multidimensional stochastic differential equations driven by a general rough noise, e.g. a fractional Brownian motion. In the…

Numerical Analysis · Mathematics 2020-06-25 Sebastian Riedel , Yue Wu

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 show that a pathwise stochastic integral with respect to fractional Brownian motion with an adapted integrand $g$ can have any prescribed distribution, moreover, we give both necessary and sufficient conditions when random variables can…

Probability · Mathematics 2013-03-22 Yuliya Mishura , Georgiy Shevchenko , Esko Valkeila

We prove that solutions of stochastic differential equations driven by fractional Brownian motion for $H>1/2$ define flows of homeomorphisms on $\mathbb{R}^{d}$.

Probability · Mathematics 2007-05-23 L. Decreusefond , D. Nualart

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 2020-08-05 Xi Geng , Cheng Ouyang , Samy Tindel

In this paper we use the chaos decomposition approach to establish the existence of a unique continuous solution to linear fractional differential equations of the Skorohod type. Here the coefficients are deterministic, the inital condition…

Probability · Mathematics 2007-06-13 Jorge A. Leon , Jaime San Martin

In this paper we show the existence and uniqueness of a solution for a stochastic differential equation driven by an additive noise which is the sum of two fractional Brownian motions with different Hurst parameters. The proofs are based on…

Probability · Mathematics 2022-07-12 David Nualart , Ercan Sönmez

In this paper, we study the existence and uniqueness of mild solution for a stochastic neutral partial functional integro-differential equation with delay in a Hilbert space driven by a fractional Brownian motion and with non-deterministic…

Probability · Mathematics 2018-09-11 B. Boufoussi , S. Hajji , S. Mouchtabih

We study existence and uniqueness of solutions to the equation $dX_t=b(X_t)dt + dB_t$, where $b$ is a distribution in some Besov space and $B$ is a fractional Brownian motion with Hurst parameter $H\leqslant 1/2$. First, the equation is…

Probability · Mathematics 2023-11-10 Lukas Anzeletti , Alexandre Richard , Etienne Tanré

We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process (not necessarily a semi-martingale). No adaptedness of initial point or vector fields is assumed. Under a simple condition on the…

Probability · Mathematics 2007-05-23 Laure Coutin , Peter Friz , Nicolas Victoir

We consider the transport equation driven by the fractional Brownian motion. We study the existence and the uniqueness of the weak solution and, by using the tools of the Malliavin calculus, we prove the existence of the density of the…

Probability · Mathematics 2014-08-28 Christian Olivera , Ciprian Tudor

In this paper we show that solutions of stochastic partial differential equations driven by Brownian motion can be approximated by stochastic partial differential equations forced by pure jump noise/random kicks. Applications to stochastic…

Probability · Mathematics 2014-01-31 Giulia Di Nunno , Tusheng Zhang

This paper is devoted to the study of hyperbolic systems of linear partial differential equations perturbed by a Brownian motion. The existence and uniqueness of solutions are proved by an energy method. The specific features of this class…

Probability · Mathematics 2021-09-29 Adnan Aboulalaa

We study the approximation of stochastic differential equations driven by a fractional Brownian motion with Hurst parameter $H>1/2$. For the mean-square error at a single point we derive the optimal rate of convergence that can be achieved…

Probability · Mathematics 2007-06-19 Andreas Neuenkirch

In this paper we show that under some assumptions, for a $d$-dimensional fractional Brownian motion with Hurst parameter $H>1/2$, the density of solution of stochastic differential equation driven by it has a short-time expansion similar to…

Probability · Mathematics 2010-05-20 Fabrice Baudoin , Cheng Ouyang

We study controlled differential equations driven by a rough path (in the sense of T. Lyons) with an additional, possibly unbounded drift term. We show that the equation induces a solution flow if the drift grows at most linearly.…

Probability · Mathematics 2016-05-19 Sebastian Riedel , Michael Scheutzow