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We consider an Ito stochastic differential equation with delay, driven by brownian motion, whose solution, by an appropriate reformulation, defines a Markov process $X$ with values in a space of continuous functions $\mathbf C$, with…

Probability · Mathematics 2013-04-10 Marco Fuhrman , Federica Masiero , Gianmario Tessitore

We investigate the validity and accuracy of weak-noise (saddle-point or instanton) approximations for piecewise-smooth stochastic differential equations (SDEs), taking as an illustrative example a piecewise-constant SDE, which serves as a…

Statistical Mechanics · Physics 2013-11-05 Yaming Chen , Adrian Baule , Hugo Touchette , Wolfram Just

We develop a Fourier approach to rough path integration, based on the series decomposition of continuous functions in terms of Schauder functions. Our approach is rather elementary, the main ingredient being a simple commutator estimate,…

Probability · Mathematics 2014-10-16 Massimiliano Gubinelli , Peter Imkeller , Nicolas Perkowski

An approach to analysis on path spaces of Riemannian manifolds is described. The spaces are furnished with `Brownian motion' measure which lies on continuous paths, though differentiation is restricted to directions given by tangent paths…

Probability · Mathematics 2023-03-07 K. D. Elworthy , Xue-Mei Li

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

In the article, the rough path theory is extended to cover paths from the exponential Besov-Orlicz space \[B^\alpha_{\Phi_\beta,q}\quad\mbox{ for }\quad \alpha\in (1/3,1/2],\,\quad \Phi_\beta(x) \sim…

Probability · Mathematics 2024-06-06 Petr Čoupek , František Hendrych , Jakub Slavík

We obtain a stochastic differential equation (SDE) satisfied by the first $n$ coordinates of a Brownian motion on the unit sphere in $\mathbb{R}^{n+\ell}$. The SDE has non-Lipschitz coefficients but we are able to provide an analysis of…

Probability · Mathematics 2018-09-14 Aleksandar Mijatović , Veno Mramor , Gerónimo Uribe Bravo

The large deviations analysis of solutions to stochastic differential equations and related processes is often based on approximation. The construction and justification of the approximations can be onerous, especially in the case where the…

Probability · Mathematics 2008-08-28 Amarjit Budhiraja , Paul Dupuis , Vasileios Maroulas

We present an algorithm for the efficient sampling of conditional paths of stochastic differential equations (SDEs). While unconditional path sampling of SDEs is straightforward, albeit expensive for high dimensional systems of SDEs,…

Numerical Analysis · Mathematics 2011-02-11 Panagiotis Stinis

The paper is concerned with the existence and uniqueness of a strong solution to a two-dimensional backward stochastic Navier-Stokes equation with nonlinear forcing, driven by a Brownian motion. We use the spectral approximation and the…

Probability · Mathematics 2011-05-02 Jinniao Qiu , Shanjian Tang , Yuncheng You

In this paper we are concerned with distribution dependent backward stochastic differential equations (DDBSDEs) driven by Gaussian processes. We first show the existence and uniqueness of solutions to this type of equations. This is done by…

Probability · Mathematics 2023-02-08 Xiliang Fan , Jiang-Lun Wu

In this work, we introduce a novel pricing methodology in general, possibly non-Markovian local stochastic volatility (LSV) models. We observe that by conditioning the LSV dynamics on the Brownian motion that drives the volatility, one…

Mathematical Finance · Quantitative Finance 2025-03-24 Peter Bank , Christian Bayer , Peter K. Friz , Luca Pelizzari

The Skorokhod embedding problem is to represent a given probability as the distribution of Brownian motion at a chosen stopping time. Over the last 50 years this has become one of the important classical problems in probability theory and a…

Probability · Mathematics 2016-05-16 Mathias Beiglboeck , Alexander M. G. Cox , Martin Huesmann

A geometric p-rough path can be seen to be a genuine path of finite p-variation with values in a Lie group equipped with a natural distance. The group and its distance lift (R^{d},+,0) and its Euclidean distance. This approach allows us to…

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

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 2020-08-03 Xi Geng , Cheng Ouyang , Samy Tindel

Backward stochastic differential equations (BSDEs) in the sense of Pardoux-Peng [Backward stochastic differential equations and quasilinear parabolic partial differential equations, Lecture Notes in Control and Inform. Sci., 176, 200--217,…

Probability · Mathematics 2010-08-03 Joscha Diehl , Peter Friz

This paper is devoted to the smooth and stationary Wong-Zakai approximations for a class of rough differential equations driven by a geometric fractional Brownian rough path $\boldsymbol{\omega}$ with Hurst index…

Probability · Mathematics 2023-03-09 Qiyong Cao , Hongjun Gao , Bjorn Schmalfuss

We study the problem of existence, uniqueness and approximation of solutions of finite dimensional Stratonovich stochastic differential equations with reflecting boundary condition driven by semimartingales with jumps. As an application we…

Probability · Mathematics 2014-11-11 Leszek Slominski

We prove pathwise nonuniqueness in the stochastic partial differential equations (SPDEs) for some one-dimensional super-Brownian motions with immigration. In contrast to a closely related case investigated by Mueller, Mytnik and Perkins…

Probability · Mathematics 2015-12-23 Yu-Ting Chen

We investigate the stochastic modified equation which plays an important role in the stochastic backward error analysis for explaining the mathematical mechanism of a numerical method. The contribution of this paper is threefold. First, we…

Numerical Analysis · Mathematics 2019-07-08 Chuchu Chen , Jialin Hong , Chuying Huang