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We introduce a canonical way of performing the joint lift of a Brownian motion $W$ and a low-regularity adapted stochastic rough path $\mathbf{X}$, extending [Diehl, Oberhauser and Riedel (2015). A L\'evy area between Brownian motion and…

Mathematical Finance · Quantitative Finance 2026-03-10 Ofelia Bonesini , Emilio Ferrucci , Ioannis Gasteratos , Antoine Jacquier

We develop the structure theory for transformations of weakly geometric rough paths of bounded $1 < p$-variation and their controlled paths. Our approach differs from existing approaches as it does not rely on smooth approximations. We…

Classical Analysis and ODEs · Mathematics 2022-09-01 Thomas Cass , Bruce K. Driver , Christian Litterer , Emilio Ferrucci

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

In this article, we show how the theory of rough paths can be used to provide a notion of solution to a class of nonlinear stochastic PDEs of Burgers type that exhibit too high spatial roughness for classical analytical methods to apply. In…

Probability · Mathematics 2010-08-11 Martin Hairer

The goal of these notes is to provide an introduction to rough partial differential equations. For this purpose, we will present the theory of rough paths to the extend as it is required. Applications to stochastic partial differential…

Probability · Mathematics 2026-05-12 Stefan Tappe

We present a new version of the stochastic sewing lemma, capable of handling multiple discontinuous control functions. This is then used to develop a theory of rough stochastic analysis in a c\`adl\`ag setting. In particular, we define…

Probability · Mathematics 2026-03-30 Andrew L. Allan , Jost Pieper

Building on the functional-analytic framework of operator-valued kernels and un-truncated signature kernels, we propose a scalable, provably convergent signature-based algorithm for a broad class of high-dimensional, path-dependent hedging…

Functional Analysis · Mathematics 2025-02-06 Nicola Muca Cirone , Cristopher Salvi

T. Lyons' rough path theory is something like a deterministic version of K. Ito's theory of stochastic differential equations, combined with ideas from K. T. Chen's theory of iterated path integrals. In this article we survey rough path…

Probability · Mathematics 2016-02-11 Yuzuru Inahama

In this paper we study the path-regularity and martingale properties of the set-valued stochastic integrals defined in our previous work Ararat et al. (2023). Such integrals have some fundamental differences from the well-known…

Probability · Mathematics 2023-08-28 Çağın Ararat , Jin Ma

Motivated by a problematic coming from mathematical finance, this paper is devoted to existing and additional results of continuity and differentiability of the It\^o map associated to rough differential equations. These regularity results…

Probability · Mathematics 2019-01-16 Nicolas Marie

Using fractional calculus we define integrals of the form $% \int_{a}^{b}f(x_{t})dy_{t}$, where $x$ and $y$ are vector-valued H\"{o}lder continuous functions of order $\displaystyle \beta \in (\frac13, \frac12)$ and $f$ is a continuously…

Probability · Mathematics 2007-05-23 Yaozhong Hu , David Nualart

In this paper, we study rough path properties of stochastic integrals of It\^{o}'s type and Stratonovich's type with respect to $G$-Brownian motion. The roughness of $G$-Brownian Motion is estimated and then the pathwise Norris lemma in…

Probability · Mathematics 2016-08-24 Shige Peng , Huilin Zhang

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

A new paradigm recently emerged in financial modelling: rough (stochastic) volatility, first observed by Gatheral et al. in high-frequency data, subsequently derived within market microstructure models, also turned out to capture…

Pricing of Securities · Quantitative Finance 2017-10-23 Christian Bayer , Peter K. Friz , Paul Gassiat , Joerg Martin , Benjamin Stemper

We present a novel perspective on the universal approximation theorem for rough path functionals, introducing a polynomial-based approximation class. We extend universal approximation to non-geometric rough paths within the tensor algebra.…

Functional Analysis · Mathematics 2025-12-23 Fabian A. Harang , Fred Espen Benth , Fride Straum

We discuss stochastic calculus for large classes of Gaussian processes, based on rough path analysis. Our key condition is a covariance measure structure combined with a classical criterion due to Jain and Monrad [Ann. Probab. 11 (1983)…

Probability · Mathematics 2016-02-11 Peter K. Friz , Benjamin Gess , Archil Gulisashvili , Sebastian Riedel

In the spirit of Marcus canonical stochastic differential equations, we study a similar notion of rough differential equations (RDEs), notably dropping the assumption of continuity prevalent in the rough path literature. A new metric is…

Probability · Mathematics 2019-02-12 Ilya Chevyrev , Peter K. Friz

The It\^o formula, originated by K. It\^o, is focus on the stochastic calculus, where many stochastic processes can be placed under the framework of rough paths. In rough path theory, It\^o formulas have been proved for rough paths with…

Probability · Mathematics 2025-03-05 Nannan Li , Xing Gao

We consider idealized financial markets in which price paths of the traded securities are cadlag functions, imposing mild restrictions on the allowed size of jumps. We prove the existence of quadratic variation for typical price paths,…

Trading and Market Microstructure · Quantitative Finance 2014-09-01 Vladimir Vovk

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