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We investigate the well-posedness of stochastic differential equations driven by fractional Brownian motion, focusing on the long-range dependent case $H \in (\frac{1}{2}, 1)$. While existing results on regularization by such noise…

Probability · Mathematics 2025-07-01 Maximilian Buthenhoff , Ercan Sönmez

This work concerns stochastic Volterra equations with singular kernels. Under the suitable conditions, we prove the central limit theorem for them. Moreover, we apply our result to stochastic Volterra equations with the kernels of…

Probability · Mathematics 2023-03-06 Huijie Qiao

Based on the recent development of the framework of Volterra rough paths, we consider here the probabilistic construction of the Volterra rough path associated to the fractional Brownian motion with $H>\frac{1}{2}$ and for the standard…

Probability · Mathematics 2022-02-11 Fabian Harang , Samy Tindel , Xiaohua Wang

We construct the basis of a stochastic calculus for so-called Volterra processes, i.e., processes which are defined as the stochastic integral of a time-dependent kernel with respect to a standard Brownian motion. For these processes which…

Probability · Mathematics 2007-05-23 L. Decreusefond

We consider convolution-type stochastic Volterra equations with additive Hilbert-valued fractional Brownian motion, $0<H<1$. We find the weak solution to this stochastic Volterra equation, and study its stochastic integral part, the…

Probability · Mathematics 2007-05-23 Peter Caithamer , Anna Karczewska

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

In this note we prove an existence and uniqueness result of solution for stochastic Volterra integral equations driven by a fractional Brownian motion with Hurst parameter H > 1/2, showing also that the solution has finite moments. The…

Probability · Mathematics 2010-03-09 Mireia Besalú , Carles Rovira

In this paper, we first study the existence-uniqueness and large deviation estimate of solutions for stochastic Volterra integral equations with singular kernels in 2-smooth Banach spaces. Then, we apply them to a large class of semilinear…

Probability · Mathematics 2008-12-05 Xicheng Zhang

We investigate stochastic Volterra equations and their limiting laws. The stochastic Volterra equations we consider are driven by a Hilbert space valued \Levy noise and integration kernels may have non-linear dependence on the current state…

Probability · Mathematics 2020-07-22 Fred Espen Benth , Nils Detering , Paul Kruehner

In this paper, the notion of singular backward stochastic Volterra integral equations (singular BSVIEs for short) in infinite dimensional space is introduced, and the corresponding well-posedness is carefully established. A class of…

Optimization and Control · Mathematics 2023-12-08 Tianxiao Wang , Mengliang Zheng

This paper is devoted to study a class of stochastic Volterra equations associated with fractional Brownian motion. We first prove the Driver type integration by parts formula and the shift Harnack type inequalities. As a direct…

Probability · Mathematics 2014-07-24 XiLiang Fan

A fast simulation framework for stochastic Volterra processes based on Random Fourier Features (RFF) approximation of the kernel is developed. After recalling the main properties of Volterra processes and reviewing existing numerical…

Mathematical Finance · Quantitative Finance 2026-05-26 Othmane Zarhali , Nicolas Langrené

We consider stochastic Volterra integral equations driven by a fractional Brownian motion with Hurst parameter H > 1/2 . We first derive supremum norm estimates for the solution and its Malliavin derivative. We then show existence and…

Probability · Mathematics 2020-04-08 Mireia Besalú , David Márquez-Carreras , Eulàlia Nualart

We consider stochastic differential equations driven by some Volterra processes. Under time reversal, these equations are transformed into past dependent stochastic differential equations driven by a standard Brownian motion. We are then in…

Probability · Mathematics 2012-12-24 Laurent Decreusefond

In this paper, we are concerned with stochastic Volterra equations with singular kernels and H\"older continuous coefficients. We first establish the well-posedness of these equations by utilising the Yamada-Watanabe approach. Then, we aim…

Probability · Mathematics 2024-07-03 Huijie Qiao , Jiang-Lun Wu

This paper provides a Feller's test for explosions of one-dimensional continuous stochastic Volterra processes of convolution type. The study focuses on dynamics governed by nonsingular kernels, which preserve the semimartingale property of…

Probability · Mathematics 2024-06-21 Alessandro Bondi , Sergio Pulido

In this work, we establish a comparison principle for stochastic Volterra equations with respect to the initial condition and the drift $b$ applicable to a wide class of Volterra kernels and input curves $g$ that may be singular at zero.…

Probability · Mathematics 2025-09-26 Ole Cañadas , Martin Friesen

Our study aims to specify the asymptotic error distribution in the discretization of a stochastic Volterra equation with a fractional kernel. It is well-known that for a standard stochastic differential equation, the discretization error,…

Numerical Analysis · Mathematics 2021-12-17 Masaaki Fukasawa , Takuto Ugai

In this article integro-differential Volterra equations whose convolution kernel depends on the vector variable are considered and a connection of these equations with a class of semi-Markov processes is established. The variable order…

Probability · Mathematics 2018-07-19 Mladen Savov , Bruno Toaldo

We study Volterra processes $X_t = \int_0^t K(t,s) dW_s$, where $W$ is a standard Wiener process, and the kernel has the form $K(t,s) = a(s) \int_s^t b(u) c(u-s) du$. This form generalizes the Volterra kernel for fractional Brownian motion…

Probability · Mathematics 2020-04-07 Yuliya Mishura , Georgiy Shevchenko , Sergiy Shklyar
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