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We consider the rough differential equation $dY=f(Y)d\bm \om$ where $\bm \om=(\omega,\bbomega)$ is a rough path defined by a Brownian motion $\omega$ on $\RR^m$. Under the usual regularity assumption on $f$, namely $f\in C^3_b (\RR^d,…

Probability · Mathematics 2020-02-25 Hongjun Gao , María J. Garrido-Atienza , Anhui Gu , Kening Lu , Björn Schmalfuss

We study fully nonlinear second-order (forward) stochastic partial differential equations (SPDEs). They can also be viewed as forward path-dependent PDEs (PPDEs) and will be treated as rough PDEs (RPDEs) under a unified framework. We…

Probability · Mathematics 2018-10-02 Rainer Buckdahn , Christian Keller , Jin Ma , Jianfeng Zhang

We establish the existence and uniqueness for a one-dimensional stochastic differential equation driven by a Brownian motion and a pure jump {\levy} process. It is shown that under fairly general conditions on the coefficients, pathwise…

Probability · Mathematics 2018-12-27 Jie Xiong , Jiayu Zheng , Xiaowen Zhou

The paper investigates existence and uniqueness for a stochastic differential equation (SDE) with distributional drift depending on the law density of the solution. Those equations are known as McKean SDEs. The McKean SDE is interpreted in…

Probability · Mathematics 2022-06-28 Elena Issoglio , Francesco Russo

The central aim of this work is to understand rough differential equations on homogeneous spaces. We focus on the formal approach, by giving an explicit expansion of the solution at each point of the real line in terms of decorated planar…

Classical Analysis and ODEs · Mathematics 2020-12-08 Charles Curry , Kurusch Ebrahimi-Fard , Dominique Manchon , Hans Z. Munthe-Kaas

A branched rough path $X$ consists of a rough integral calculus for $X \colon [0, T] \to \mathbb R^d$ which may fail to satisfy integration by parts. Using Kelly's bracket extension [Kel12], we define a notion of pushforward of branched…

Classical Analysis and ODEs · Mathematics 2023-11-29 Emilio Ferrucci

In this article we study a class of stochastic functional differential equations driven by L\'{e}vy processes (in particular, $\alpha$-stable processes), and obtain the existence and uniqueness of Markov solutions in small time intervals.…

Probability · Mathematics 2012-11-30 Xicheng Zhang

We prove existence and pathwise uniqueness results for four different types of stochastic differential equations (SDEs) perturbed by the past maximum process and/or the local time at zero. Along the first three studies, the coefficients are…

Probability · Mathematics 2010-03-31 Rachid Belfadli , Said Hamadéne , Youssef Ouknine

In this paper we prove the derivative process of a rough differential equation driven by Brownian rough path has finite $L^r$-moment for any $r /ge 1$. Thanks to Burkholder-Davis-Gundy's inequality, this kind of problem is easy in the usual…

Probability · Mathematics 2010-07-28 Yuzuru Inahama

In this paper, we establish the theory of nonlinear rough paths. We give the definition of nonlinear rough paths, and develop the integrals. Then, we study differential equations driven by nonlinear rough paths. Afterwards, we compare the…

Probability · Mathematics 2019-04-29 David Nualart , Panqiu Xia

We give meaning to differential equations with a rough path term and a Brownian noise term as driving signals. Such differential equations as well as the question of regularity of the solution map arise naturally and we discuss two…

Probability · Mathematics 2014-01-03 Joscha Diehl , Harald Oberhauser , Sebastian Riedel

In this paper, practically computable low-order approximations of potentially high-dimensional differential equations driven by geometric rough paths are proposed and investigated. In particular, equations are studied that cover the linear…

Numerical Analysis · Mathematics 2023-07-03 Martin Redmann , Sebastian Riedel

We develop a general framework for pathwise stochastic integration that extends F\"ollmer's classical approach beyond gradient-type integrands and standard left-point Riemann sums and provides pathwise counterparts of It\^o, Stratonovich,…

Probability · Mathematics 2025-07-24 Purba Das , Anna P. Kwossek , David J. Prömel

Spatial differentiability of solutions of stochastic differential equations (SDEs) is a classical question in stochastic analysis. The case of coefficients with globally Lipschitz continuous derivatives is well understood in the literature.…

Probability · Mathematics 2022-04-27 Anselm Hudde , Martin Hutzenthaler , Sara Mazzonetto

We consider the rough differential equation with drift driven by a Gaussian geometric rough path. Under natural conditions on the rough path, namely non-determinism, and uniform ellipticity conditions on the diffusion coefficient, we prove…

Probability · Mathematics 2024-02-15 Rémi Catellier , Romain Duboscq

We consider stochastic differential equations on $\mathbb R^d$ with coefficients depending on the path and distribution for the whole history. Under a local integrability condition on the time-spatial singular drift, the well-posedness and…

Probability · Mathematics 2025-07-15 Feng-Yu Wang , Chenggui Yuan , Xiao-Yu Zhao

By using a change of scale and space, we study a class of stochastic differential equations (SDEs) whose solutions are drift--perturbed and exhibit behaviour analogous to standard Brownian motion including to the Law of the Iterated…

Probability · Mathematics 2013-10-11 John A. D. Appleby , Huizhong Appleby-Wu

We provide a theory of manifold-valued rough paths of bounded 3 > p-variation, which we do not assume to be geometric. Rough paths are defined in charts, and coordinate-free (but connection-dependent) definitions of the rough integral of…

Classical Analysis and ODEs · Mathematics 2022-09-01 John Armstrong , Damiano Brigo , Thomas Cass , Emilio Ferrucci

The (strong and weak) well-posedness is proved for singular SDEs depending on the distribution density point-wisely and globally, where the drift satisfies a local integrability condition in time-spatial variables, and is Lipschitz…

Probability · Mathematics 2023-09-11 Feng-Yu Wang

Rough path theory is focused on capturing and making precise the interactions between highly oscillatory and non-linear systems. It draws on the analysis of LC Young and the geometric algebra of KT Chen. The concepts and the uniform…

Probability · Mathematics 2014-05-20 Terry Lyons