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In this paper, we first establish the existence, uniqueness and H\"older continuity of the solution to stochastic Volterra integral equations with weakly singular kernels. Then, we propose a $\theta$-Euler-Maruyama scheme and a Milstein…

Numerical Analysis · Mathematics 2020-04-13 Min Li , Chengming Huang , Yaozhong Hu

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

We combine the rough path theory and stochastic backward error analysis to develop a new framework for error analysis on numerical schemes. Based on our approach, we prove that the almost sure convergence rate of the modified Milstein…

Numerical Analysis · Mathematics 2021-03-23 Chuying Huang

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

The purpose of this paper is to establish the convergence in distribution of the normalized error in the Euler approximation scheme for stochastic Volterra equations driven by a standard Brownian motion, with a kernel of the form…

Probability · Mathematics 2022-04-18 David Nualart , Bhargobjyoti Saikia

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 paper presents the error analysis of numerical methods on graded meshes for stochastic Volterra equations with weakly singular kernels. We first prove a novel regularity estimate for the exact solution via analyzing the associated…

Numerical Analysis · Mathematics 2023-09-01 Xinjie Dai , Jialin Hong , Derui Sheng

A Milstein-type scheme was proposed to improve the rate of convergence of its approximation of the solution to a stochastic differential equation driven by a vector of continuous semimartingales. A necessary and sufficient condition was…

Probability · Mathematics 2007-05-23 Liqing Yan

We study discrete-time simulation schemes for stochastic Volterra equations, namely the Euler and Milstein schemes, and the corresponding Multi-Level Monte-Carlo method. By using and adapting some results from Zhang [22], together with the…

Numerical Analysis · Mathematics 2022-03-08 Alexandre Richard , Xiaolu Tan , Fan Yang

We propose a tamed-adaptive Milstein scheme for stochastic differential equations in which the first-order derivatives of the coefficients are locally H\"older continuous of order $\alpha$. We show that the scheme converges in the…

Probability · Mathematics 2025-07-10 Thi-Huong Vu , Hoang-Long Ngo , Duc-Trong Luong , Tran Ngoc Khue

This paper is devoted to proving a (Lindeberg-Feller type ) central limit theorem for the multilevel Monte Carlo estimator associated with the Euler discretization scheme for the stochastic Volterra equations with fractional kernels…

Probability · Mathematics 2025-06-05 Shanqi Liu , Yaozhong Hu , Hongjun Gao

For a stochastic differential equation driven by a fractional Brownian motion with Hurst parameter $H> \frac12$ it is known that the classical Euler scheme has the rate of convergence $2H-1$. In this paper we introduce a new numerical…

Probability · Mathematics 2017-03-07 Yaozhong Hu , Yanghui Liu , David Nualart

This article studies the temporal approximation of hyperbolic semilinear stochastic evolution equations with multiplicative Gaussian noise by Milstein-type schemes. We take the term hyperbolic to mean that the leading operator generates a…

Numerical Analysis · Mathematics 2026-02-03 Felix Kastner , Katharina Klioba

We study the strong approximation of a rough volatility model, in which the log-volatility is given by a fractional Ornstein-Uhlenbeck process with Hurst parameter $H<1/2$. Our methods are based on an equidistant discretization of the…

Probability · Mathematics 2016-06-14 Andreas Neuenkirch , Taras Shalaiko

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

We study the approximation of stochastic differential equations driven by a fractional Brownian motion with Hurst parameter $H>1/2$. For the mean-square error at a single point we derive the optimal rate of convergence that can be achieved…

Probability · Mathematics 2007-06-19 Andreas Neuenkirch

For a class of stochastic models with Gaussian and rough mean-reverting volatility that embeds the genuine rough Stein-Stein model, we study the weak approximation rate when using a Euler type scheme with integrated kernels. Our first…

Probability · Mathematics 2026-02-23 Aurélien Alfonsi , Ahmed Kebaier

In this paper, we investigate and analyze numerical solutions for the Volterra integrodifferential equations with tempered multi-term kernels. Firstly we derive some regularity estimates of the exact solution. Then a temporal-discrete…

Numerical Analysis · Mathematics 2023-05-03 Wenlin Qiu

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

Simulation of rough volatility models involves discretization of stochastic integrals where the integrand is a function of a (correlated) fractional Brownian motion of Hurst index $H \in (0,1/2)$. We obtain results on the rate of…

Computational Finance · Quantitative Finance 2023-02-07 Paul Gassiat
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