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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

In this work, weakly corrected explicit, semi-implicit and implicit Milstein approximations are presented for the solution of nonlinear stochastic differential equations. The solution trajectories provided by the Milstein schemes are…

Numerical Analysis · Mathematics 2021-08-25 Tapas Tripura , Budhaditya Hazra , Souvik Chakraborty

In this paper, the Milstein method is used to approximate invariant measures of stochastic differential equations with commutative noise. The decay rate of the transition probability kernel generated by the Milstein method to the unique…

Numerical Analysis · Mathematics 2019-01-28 Lihui Weng , Wei Liu

In this article, we propose an implicit finite difference scheme for a two-dimensional parabolic stochastic partial differential equation (SPDE) of Zakai type. The scheme is based on a Milstein approximation to the stochastic integral and…

Numerical Analysis · Mathematics 2018-11-29 Christoph Reisinger , Zhenru Wang

We study the $L^p$ rate of convergence of the Milstein scheme for SDEs when the drift coefficients possess only H\"older regularity. If the diffusion is elliptic and sufficiently regular, we obtain rates consistent with the additive case.…

Probability · Mathematics 2024-12-12 Máté Gerencsér , Gerald Lampl , Chengcheng Ling

In this article, we propose a Milstein finite difference scheme for a stochastic partial differential equation (SPDE) describing a large particle system. We show, by means of Fourier analysis, that the discretisation on an unbounded domain…

Numerical Analysis · Mathematics 2012-04-09 Michael B. Giles , Christoph Reisinger

We study strong approximation of $d$-dimensional stochastic differential equations (SDEs) with a discontinuous drift coefficient driven by a $d$-dimensional Brownian motion $W$. More precisely, we essentially assume that the drift…

Probability · Mathematics 2025-05-22 Christopher Rauhögger

We extend the taming techniques developed in \cite{konstantinos2014,sabanis2013} to construct explicit Milstein schemes that numerically approximate L\'evy driven stochastic differential equations with super-linearly growing drift…

Probability · Mathematics 2015-12-24 Chaman Kumar , Sotirios Sabanis

In the study of McKean-Vlasov stochastic differential equations (MV-SDEs), numerical approximation plays a crucial role in understanding the behavior of interacting particle systems (IPS). Classical Milstein schemes provide strong…

Numerical Analysis · Mathematics 2025-10-21 Jingtao Zhu , Yuying Zhao , Siqing Gan

In this paper, we first derive Milstein schemes for an interacting particle system associated with point delay McKean-Vlasov stochastic differential equations (McKean-Vlasov SDEs), possibly with a drift term exhibiting super-linear growth…

Numerical Analysis · Mathematics 2023-06-21 Jianhai Bao , Christoph Reisinger , Panpan Ren , Wolfgang Stockinger

We present a novel multilevel Monte Carlo approach for estimating quantities of interest for stochastic partial differential equations (SPDEs). Drawing inspiration from [Giles and Szpruch: Antithetic multilevel Monte Carlo estimation for…

Numerical Analysis · Mathematics 2025-04-15 Abdul-Lateef Haji-Ali , Andreas Stein

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 investigate existence and uniqueness of strong solutions of mean-field stochastic differential equations with irregular drift coefficients. Our direct construction of strong solutions is mainly based on a compactness criterion employing…

Probability · Mathematics 2018-07-02 Martin Bauer , Thilo Meyer-Brandis , Frank Proske

This paper concerns the numerical approximation for the invariant distribution of Markovian switching L\'evy-driven stochastic differential equations. By combining the tamed-adaptive Euler-Maruyama scheme with the Multi-level Monte Carlo…

Probability · Mathematics 2024-11-07 Hoang-Viet Nguyen , Trung-Thuy Kieu , Duc-Trong Luong , Hoang-Long Ngo , Tran Ngoc Khue

A conjecture appears in \cite{milsteinscheme}, in the form of a remark, where it is stated that it is possible to construct, in a specified way, any high order explicit numerical schemes to approximate the solutions of SDEs with superlinear…

Probability · Mathematics 2018-11-07 Sotirios Sabanis , Ying Zhang

We propose a new explicit numerical scheme for stochastic differential equation with super-linearly growing drift and linearly growing diffusion coefficients which are also twice continuously differentiable. The rate of strong convergence…

Probability · Mathematics 2018-06-04 Tejinder Kumar , Chaman Kumar

We introduce a class of explicit balanced schemes for stochastic differential equations with coefficients of superlinearly growth satisfying a global monotone condition. The first scheme is a balanced Euler scheme and is of order half in…

Numerical Analysis · Mathematics 2017-05-23 Zhongqiang Zhang , Heping Ma

We consider the approximation of stochastic differential equations (SDEs) with non-Lipschitz drift or diffusion coefficients. We present a modified explicit Euler-Maruyama discretisation scheme that allows us to prove strong convergence,…

Computational Finance · Quantitative Finance 2016-04-12 Jean-Francois Chassagneux , Antoine Jacquier , Ivo Mihaylov

We demonstrate an approach to the numerical solution of nonlinear stochastic differential equations with Markovian switching. Such equations describe the stochastic dynamics of processes where the drift and diffusion coefficients are…

Numerical Analysis · Mathematics 2024-08-28 Cónall Kelly , Kate O'Donovan

A class of implicit Milstein type methods is introduced and analyzed in the present article for stochastic differential equations (SDEs) with non-globally Lipschitz drift and diffusion coefficients. By incorporating a pair of method…

Numerical Analysis · Mathematics 2023-03-21 Xiaojie Wang