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Related papers: Ramification of Volterra-type Rough Paths

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We introduce affine Volterra processes, defined as solutions of certain stochastic convolution equations with affine coefficients. Classical affine diffusions constitute a special case, but affine Volterra processes are neither…

Probability · Mathematics 2019-10-23 Eduardo Abi Jaber , Martin Larsson , Sergio Pulido

Pathwise uniqueness is established for a class of one-dimensional stochastic Volterra equations driven by Brownian motion with singular kernels and H\"older continuous diffusion coefficients. Consequently, the existence of unique strong…

Probability · Mathematics 2025-03-03 David J. Prömel , David Scheffels

We propose the numerical methods for solution of the weakly regular linear and nonlinear evolutionary (Volterra) integral equation of the first kind. The kernels of such equations have jump discontinuities along the continuous curves…

Numerical Analysis · Mathematics 2015-07-24 Ildar Muftahov , Aleksandr Tynda , Denis Sidorov

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

Rough paths techniques give the ability to define solutions of stochastic differential equations driven by signals $X$ which are not semimartingales and whose $p$-variation is finite only for large values of $p$. In this context, rough…

Probability · Mathematics 2020-05-15 Yanghui Liu , Zachary Selk , Samy Tindel

Volterra functions were introduced at the beginning of the twentieth century as solutions of some integral equations of convolution type with logarithmic kernel. Since then, few authors have studied this family of functions and faced with…

Complex Variables · Mathematics 2016-10-06 Roberto Garrappa , Francesco Mainardi

We propose a new theoretical framework that exploits convolution kernels to transform a Volterra-type path-dependent (non-Markovian) stochastic process into a standard (Markovian) diffusion process. Remarkably, it is also possible to go…

Mathematical Finance · Quantitative Finance 2025-10-10 Ofelia Bonesini , Giorgia Callegaro , Martino Grasselli , Gilles Pagès

This note is devoted to construct a rough path above a multidimensional fractional Brownian motion $B$ with any Hurst parameter $H\in(0,1)$, by means of its representation as a Volterra Gaussian process. This approach yields some algebraic…

Probability · Mathematics 2011-11-10 David Nualart , Samy Tindel

The stack of iterated integrals of a path is embedded in a larger algebraic structure where iterated integrals are indexed by decorated rooted trees and where an extended Chen's multiplicative property involves the D\"urr-Connes-Kreimer…

Classical Analysis and ODEs · Mathematics 2007-05-23 M. Gubinelli

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

We prove existence and uniqueness results for (mild) solutions to some non-linear parabolic evolution equations with a rough forcing term. Our method of proof relies on a careful exploitation of the interplay between the spatial and time…

Probability · Mathematics 2009-11-03 Thomas Cass , Zhongmin Qian , Jan Tudor

In this text matrix Volterra integral equation of the first kind is addressed. It is assumed that kernels of the equation have jump discontinuities on non-intersecting curves. Such equations appear in the theory of evolving dynamic systems.…

Dynamical Systems · Mathematics 2012-09-03 Denis Sidorov

Several methods for solving efficiently the one-dimensional deconvolution problem are proposed. The problem is to solve the Volterra equation ${\mathbf k} u:=\int_0^t k(t-s)u(s)ds=g(t),\quad 0\leq t\leq T$. The data, $g(t)$, are noisy. Of…

Numerical Analysis · Mathematics 2025-10-20 Alexander G. Ramm , A. Galstian

In the paper stochastic Volterra equations of nonscalar type in Hilbert space are studied. The aim of the paper is to provide some results on stochastic convolution and mild solutions to those Volterra equations. The motivation of the paper…

Probability · Mathematics 2007-05-23 Anna Karczewska

Motivated by the recent advances in the theory of stochastic partial differential equations involving nonlinear functions of distributions, like the Kardar-Parisi-Zhang (KPZ) equation, we reconsider the unique solvability of one-dimensional…

Probability · Mathematics 2015-03-09 François Delarue , Roland Diel

We establish new weak existence results for $d$-dimensional Stochastic Volterra Equations (SVEs) with continuous coefficients and possibly singular one-dimensional non-convolution kernels. These results are obtained by introducing an…

Probability · Mathematics 2026-05-14 Eduardo Abi Jaber , Aurélien Alfonsi , Guillaume Szulda

The aim of this paper is to provide a comprehensive analysis of the path-dependent Stochastic Volterra Integral Equations (SVIEs), in which both the drift and the diffusion coefficients are allowed to depend on the whole trajectory of the…

Probability · Mathematics 2026-04-10 Emmanuel Gnabeyeu , Gilles Pagès

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

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

We introduce the (path-valued) Brownian frame process whose evaluation at time t is the sample path of the underlying Brownian motion run from time t-1 to t. Due to its connections with Gaussian Volterra processes and SDDEs this is an…

Probability · Mathematics 2007-05-23 Benjamin Hoff