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Path integrals are a ubiquitous tool in theoretical physics. However, their use is sometimes hindered by the lack of control on various manipulations -- such as performing a change of the integration path -- one would like to carry out in…

Statistical Mechanics · Physics 2023-04-21 Thibaut Arnoulx de Pirey , Leticia F. Cugliandolo , Vivien Lecomte , Frédéric van Wijland

We study solutions to backward differential equations that are driven hybridly by a deterministic discontinuous rough path $W$ of finite $q$-variation for $q \in [1, 2)$ and by Brownian motion $B$. To distinguish between integration of…

Probability · Mathematics 2025-05-28 Dirk Becherer , Yuchen Sun

This paper considers possible price paths of a financial security in an idealized market. Its main result is that the variation index of typical price paths is at most 2, in this sense, typical price paths are not rougher than typical paths…

General Finance · Quantitative Finance 2016-11-29 Vladimir Vovk

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

We introduce in this work a concept of rough driver that somehow provides a rough path-like analogue of an enriched object associated with time-dependent vector fields. We use the machinery of approximate flows to build the integration…

Probability · Mathematics 2018-03-20 I. Bailleul , S. Riedel

We define a deterministic integral with respect to irregular paths as a limit of standard line integrals and completely describe a class of all paths for which this integral exists for functions with H\"older exponent in the range of (0,1].…

Classical Analysis and ODEs · Mathematics 2023-09-13 Yevgeniy Guseynov

We give meaning to linear and semi-linear (possibly degenerate) parabolic partial differential equations with (affine) linear rough path noise and establish stability in a rough path metric. In the case of enhanced Brownian motion (Brownian…

Probability · Mathematics 2013-01-17 Peter Friz , Harald Oberhauser

We construct in this article an explicit geometric rough path over arbitrary $d$-dimensional paths with finite $1/\alpha$-variation for any $\alpha\in(0,1)$. The method may be coined as 'Fourier normal ordering', since it consists in a…

Probability · Mathematics 2015-05-13 J. Unterberger

Existence and uniqueness for rough flows, transport and continuity equations driven by general geometric rough paths are established.

Analysis of PDEs · Mathematics 2021-10-05 Carlo Bellingeri , Ana Djurdjevac , Peter K. Friz , Nikolas Tapia

In this work, we introduce a solution theory for scalar-valued rough differential equations driven by multi-indices rough paths. To achieve this task, we will show how the flow approach using the log-ODE method introduced by Bailleul fits…

Probability · Mathematics 2026-01-19 Carlo Bellingeri , Yvain Bruned , Yingtong Hou

We study a class of controlled rough differential equations. It is shown that the value function satisfies a HJB type equation; we also establish a form of the Pontryagin maximum principle. Deterministic problems of this type arise in the…

Probability · Mathematics 2013-05-21 Joscha Diehl , Peter Friz , Paul Gassiat

We prove a large deviation principle for the slow-fast rough differential equations under the controlled rough path framework. The driver rough paths are lifted from the mixed fractional Brownian motion with Hurst parameter $H\in…

Probability · Mathematics 2025-02-05 Xiaoyu Yang , Yong Xu

Donsker's invariance principle is shown to hold for random walks in rough path topology. As application, we obtain Donsker-type weak limit theorems for stochastic integrals and differential equations.

Probability · Mathematics 2008-10-16 Emmanuel Breuillard , Peter Friz , Martin Huesmann

We show how the flow approach of Duch, with elementary differentials as coordinates, can be used to prove well-posedness for rough stochastic differential equations driven by fractional Brownian motion with Hurst index $H > \frac{1}{4}$. A…

Probability · Mathematics 2026-03-03 Ajay Chandra , Léonard Ferdinand

Rough path analysis is developed in the full Besov scale. This extends, and essentially concludes, an investigation started by [Pr\"omel--Trabs, Rough differential equations driven by signals in {B}esov spaces. J. Diff. Equ. 2016], further…

Probability · Mathematics 2021-05-14 Peter Friz , Benjamin Seeger

In this paper, we study two variations of the time discrete Taylor schemes for rough differential equations and for stochastic differential equations driven by fractional Brownian motions. One is the incomplete Taylor scheme which excludes…

Probability · Mathematics 2015-10-30 Yaozhong Hu , Yanghui Liu , David Nualart

In this paper, we propose a method of fundamental solutions for the problems of two-dimensional potential flow past a doubly-periodic array of obstacles. The solutions of these problems involve doubly-periodic functions, and it is difficult…

Numerical Analysis · Mathematics 2020-06-30 Hidenori Ogata

In this article we consider rough differential equations (RDEs) driven by non-geometric rough paths, using the concept of branched rough paths introduced in Gubinelli (2004). We first show that branched rough paths can equivalently be…

Probability · Mathematics 2014-01-08 Martin Hairer , David Kelly

We give an overview of the recent approach to the integration of rough paths that reduces the problem to classical Young integration. As an application, we extend an argument of Schwartz to rough differential equations, and prove the…

Classical Analysis and ODEs · Mathematics 2015-06-15 Terry Lyons , Danyu Yang

The theory of one-dimensional stochastic differential equations driven by Brownian motion is classical and has been largely understood for several decades. For stochastic differential equations with jumps the picture is still incomplete,…

Probability · Mathematics 2020-12-15 Sam Baguley , Leif Doering , Andreas Kyprianou
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