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We investigate the properties of the solutions of scaled Volterra equations (i.e. with an affine mean-reverting drift) in terms of stationarity at both a finite horizon and on the long run. In particular we prove that such an equation never…

Probability · Mathematics 2025-08-28 Gilles Pagès

We consider a Volterra convolution equation in $\mathbb{R}^d$ perturbed with an additive fractional Brownian motion of Riemann-Liouville type with Hurst parameter $H\in (0,1)$. We show that its solution solves a stochastic partial…

Probability · Mathematics 2023-09-26 Alessandro Bondi , Franco Flandoli

Given a fractional Brownian motion \,\,$(B_{t}^{H})_{t\geq 0}$,\, with Hurst parameter \,$> 1/2$\,\,we study the properties of all solutions of \,\,: {equation} X_{t}=B_{t}^{H}+\int_0^t X_{u}d\mu(u), \;\; 0\leq t\leq 1{equation} A different…

Probability · Mathematics 2011-07-20 Mamadou Abdoul Diop , Youssef Ouknine

Some results about existence, uniqueness, and attractive behaviour of solutions for nonlinear Volterra integral equations with non-convolution kernels are presented in this paper. These results are based on similar ones about nonlinear…

Analysis of PDEs · Mathematics 2016-08-14 M. R. Arias , R. Benítez , V. J. Bolós

In this work, we consider the regularity property of stochastic convolutions for a class of abstract linear stochastic retarded functional differential equations with unbounded operator coefficients. We first establish some useful estimates…

Probability · Mathematics 2019-06-04 Kai Liu

We prove existence and uniqueness of the solution of a stochastic shell--model. The equation is driven by an infinite dimensional fractional Brownian--motion with Hurst--parameter $H\in (1/2,1)$, and contains a non--trivial coefficient in…

Analysis of PDEs · Mathematics 2014-10-27 Hakima Bessaih , María J. Garrido-Atienza , Björn Schmalfuss

This paper studies a stochastic functional differential equation driven by a fractional Brownian motion with Hurst parameter H>1/2, constrained to be reflected at 0. We prove the existence of solutions using the Euler method. However,…

Probability · Mathematics 2024-10-02 Chadad Monir

Explicit solutions for a class of linear backward stochastic differential equations (BSDE) driven by Gaussian Volterra processes are given. These processes include the multifractional brownian motion and the multifractional…

Probability · Mathematics 2019-12-03 Habiba Knani , Marco Dozzi

We establish Burkholder-Davis-Gundy-type inequalities for stochastic Volterra integrals with a completely monotone convolution kernel, which may exhibit singular behaviour at the origin. When the supremum is taken over a finite interval,…

Probability · Mathematics 2025-04-01 Alexandre Pannier

In this paper, we consider a general class of stochastic Volterra equations with small noise. Our aim is to study the fluctuation of the solution around its deterministic limit. We use the techniques of Malliavin calculus to show that the…

Probability · Mathematics 2026-04-07 N. T. Dung , N. T. Hang

We define weighted fractional Brownian sheets, which are a class of Gaussian random fields with four parameters that include fractional Brownian sheets as special cases, and we give some of their properties. We show that for certain values…

Probability · Mathematics 2008-12-01 Johanna Garzón

We discuss the application of multistep collocation methods to Volterra integral equations which contain a weakly singular kernel $(t-\tau)^{\alpha-1}$ with $0 <\alpha <1.$ Convergence orders of the methods are determined and their…

Numerical Analysis · Mathematics 2014-12-17 D. Nazari Susahab , S. Shahmorad

The theory of affine processes has been recently extended to the framework of stochastic Volterra equations with continuous trajectories. These so-called affine Volterra processes overcome modeling shortcomings of affine processes because…

Probability · Mathematics 2022-03-15 Alessandro Bondi , Giulia Livieri , Sergio Pulido

In this paper, our work is devoted to studying Volterra type McKean-Vlasov stochastic differential equations with singular kernels. Firstly, the well-posedness of Volterra type McKean-Vlasov stochastic differential equations are…

Probability · Mathematics 2023-11-14 Shanqi Liu , Hongjun Gao

We provide a unified treatment of pathwise Large and Moderate deviations principles for a general class of multidimensional stochastic Volterra equations with singular kernels, not necessarily of convolution form. Our methodology is based…

Probability · Mathematics 2022-04-15 Antoine Jacquier , Alexandre Pannier

We study a compound Poisson (random time-change) approximation for stochastic differential equations (SDEs) and stochastic Volterra equations whose coefficients may be merely measurable in time and may even exhibit integrable singularities.…

Probability · Mathematics 2026-03-10 Xicheng Zhang , Yuanlong Zhao

Based on the notion of paracontrolled distributions, we provide existence and uniqueness results for rough Volterra equations of convolution type with potentially singular kernels and driven by the newly introduced class of convolutional…

Probability · Mathematics 2021-09-21 David J. Prömel , Mathias Trabs

In this article, we construct unique strong solutions to a class of stochastic Volterra differential equations driven by a singular drift vector field and a Wiener noise. Further, we examine the Sobolev differentiability of the strong…

Probability · Mathematics 2026-05-12 Emmanuel Coffie , Olivier Menoukeu-Pamen , Frank Proske

We define and solve Volterra equations driven by an irregular signal, by means of a variant of the rough path theory called algebraic integration. In the Young case, that is for a driving signal with H\"older exponent greater than 1/2, we…

Probability · Mathematics 2008-09-12 Aurélien Deya , Samy Tindel

This paper focuses on the randomized Milstein scheme for approximating solutions to stochastic Volterra integral equations with weakly singular kernels, where the drift coefficients are non-differentiable. An essential component of the…

Numerical Analysis · Mathematics 2023-12-07 Zhaohang Wang , Zhuoqi Liu , Shuaibin Gao , Junhao Hu