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We survey recent developments in the field of complexity of pathwise approximation in $p$-th mean of the solution of a stochastic differential equation at the final time based on finitely many evaluations of the driving Brownian motion.…

Probability · Mathematics 2024-03-04 T. Müller-Gronbach , L. Yaroslavtseva

The aim of this paper is to develop a general method for constructing approximation schemes for viscosity solutions of fully nonlinear pathwise stochastic partial differential equations, and for proving their convergence. Our results apply…

Analysis of PDEs · Mathematics 2019-11-01 Benjamin Seeger

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

We derive an asymptotic expansion for the quadratic variation of a stochastic process satisfying a stochastic differential equation driven by a fractional Brownian motion, based on the theory of asymptotic expansion of Skorohod integrals…

Probability · Mathematics 2022-06-02 Hayate Yamagishi , Nakahiro Yoshida

Strong approximations of uniform transport processes to the standard Brownian motion rely on the Skorokhod embedding of random walk with centered double exponential increments. In this note we make such an embedding explicit by means of a…

Probability · Mathematics 2020-02-04 Giang T. Nguyen , Oscar Peralta

Motivated by the need to develop a general framework for performing statistical inference for discretely observed random rough differential equations, our aim is to construct a geometric $p$-rough path ${\bf X}$ whose response $Y$, when…

Classical Analysis and ODEs · Mathematics 2026-03-30 Thomas Morrish , Theodore Papamarkou , Anastasia Papavasiliou , Yang Zhao

We provide a draft of a theory of geometric integration of rough differential forms which are generalizations of classical (smooth) differential forms to similar objects with very low regularity, for instance, involving H\"older continuous…

Differential Geometry · Mathematics 2020-01-20 Eugene Stepanov , Dario Trevisan

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

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

Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration…

Numerical Analysis · Mathematics 2020-06-24 Panos Stinis , Huan Lei , Jing Li , Hui Wan

Using rough path theory, we provide a pathwise foundation for stochastic It\^o integration, which covers most commonly applied trading strategies and mathematical models of financial markets, including those under Knightian uncertainty. To…

Probability · Mathematics 2024-01-04 Andrew L. Allan , Chong Liu , David J. Prömel

We go ahead with the study initiated in [3] about a heat-equation model with non-linear perturbation driven by a space-time fractional noise. Using general results from Hairer's theory of regularity structures, the analysis reduces to the…

Probability · Mathematics 2016-07-20 Aurélien Deya

The problem of the Taylor-Ito and Taylor-Stratonovich expansions of the Ito stochastic processes in a neighborhood of a fixed moment of time is considered. The classical forms of the Taylor-Ito and Taylor-Stratonovich expansions are…

Probability · Mathematics 2026-02-13 Dmitriy F. Kuznetsov

We provide an It\^{o}'s formula for stochastic dynamical equation on general time scales. Based on this It\^{o}'s formula we give a closed form expression for stochastic exponential on general time scales. We then demonstrate a Girsanov's…

Probability · Mathematics 2017-03-31 Wenqing Hu

We give a conjectural formula for sheaves supported on (irreducible) conormal varieties inside the cotangent bundle of the Grassmannian, such that their equivariant $K$-class is given by the partition function of an integrable loop model,…

Algebraic Geometry · Mathematics 2016-12-15 A. Knutson , P. Zinn-Justin

We establish a new scale of $p$-variation estimates for martingale paraproducts, martingale transforms, and It\^o integrals, of relevance in rough paths theory, stochastic, and harmonic analysis. As an application, we introduce rough…

Probability · Mathematics 2023-03-22 Peter Friz , Pavel Zorin-Kranich

We give a proof of the strong existence and the regularity of stochastic differential equations driven by a Brownian motion and a measurable, Markovian drift without no regularity hypothesis except that the Girsanov exponential associated…

Probability · Mathematics 2025-08-05 Ali Suleyman Ustunel

This work focuses on the Laplace approximation for the rough differential equation (RDE) driven by mixed rough path with as . Firstly, based on geometric rough path lifted from mixed fractional Brownian motion (fBm), the Schilder-type large…

Probability · Mathematics 2022-06-14 Xiaoyu Yang , Yong Xu , Bin Pei

In this paper we show that a path-wise solution to the following integral equation $$ Y_t = \int_0^t f(Y_t) dX_t \qquad Y_0=a \in \R^d $$ exists under the assumption that X_t is a L\'evy process of finite p-variation for some $p \geq1$ and…

Probability · Mathematics 2007-05-23 David R. E. Williams

We derive a Gronwall type inequality for mild solutions of non-autonomous parabolic rough partial differential equations (RPDEs). This inequality together with an analysis of the Cameron-Martin space associated to the noise, allows us to…

Probability · Mathematics 2025-10-30 Alexandra Blessing , Mazyar Ghani Varzaneh , Tim Seitz