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We study the error between the exact solution and its Euler-Maruyama approximation in temporal-spatial H\"older-norms for L\'evy-driven stochastic differential equations.

Probability · Mathematics 2026-05-12 Vu Thi Hue , Ngoc Khue Tran , Hoang-Long Ngo

Euler-Maruyama method is studied to approximate stochastic differential equations driven by the symmetric $\alpha$-stable additive noise with the $\beta$ H\"older continuous drift coefficient. When $\alpha \in (1,2)$ and $\beta \in…

Numerical Analysis · Mathematics 2024-12-20 Wei Liu

An Euler-type framework with equidistant step sizes is proposed for a class of time-changed stochastic differential equations.We establish the strong convergence rate of the standard Euler--Maruyama method under the global Lipschitz…

Numerical Analysis · Mathematics 2026-03-12 Ruchun Zuo

We consider the Euler-Maruyama approximation for multi-dimensional stochastic differential equations with irregular coefficients. We provide the rate of strong convergence where the possibly discontinuous drift coefficient satisfies a…

Probability · Mathematics 2014-04-11 Hoang-Long Ngo , Dai Taguchi

We study the strong rates of the Euler-Maruyama approximation for one dimensional stochastic differential equations whose drift coefficient may be neither continuous nor one-sided Lipschitz and diffusion coefficient is H\"older continuous.…

Probability · Mathematics 2016-07-21 Hoang-Long Ngo , Dai Taguchi

In this paper we study the strong convergence for the Euler-Maruyama approximation of a class of stochastic differential equations whose both drift and diffusion coefficients are possibly discontinuous.

Probability · Mathematics 2016-09-02 Hoang-Long Ngo , Dai Taguchi

In this paper, we consider a numerical approximation of the stochastic differential equation (SDE) $$X_{t}=x_{0}+ \int_{0}^{t} b(s, X_{s}) \mathrm{d}s + L_{t},~x_{0} \in \mathbb{R}^{d},~t \in [0,T],$$ where the drift coefficient $b:[0,T]…

Probability · Mathematics 2016-05-24 Olivier Menoukeu Pamen , Dai Taguchi

In this paper, we consider the weak convergence of the Euler-Maruyama approximation for one dimensional stochastic differential equations involving the local times of the unknown process. We use a transformation in order to remove the local…

Numerical Analysis · Mathematics 2017-01-18 Mohsine Benabdallah , Kamal Hiderah

In this paper, we provide the strong rate of convergence for the Euler--Maruyama scheme for multi-dimensional stochastic differential equations with uniformly locally (unbounded) H\"older continuous drift and multiplicative noise. Our…

Probability · Mathematics 2026-01-09 Tsukasa Moritoki , Dai Taguchi

We study the strong $L^p$-convergence rates of the Euler-Maruyama method for stochastic differential equations driven by Brownian motion with low-regularity drift coefficients. Specifically, the drift is assumed to be in the…

Probability · Mathematics 2025-08-15 Jinlong Wei , Junhao Hu , Guangying Lv , Chenggui Yuan

This manuscript is dedicated to the numerical approximation of super-linear slow-fast stochastic differential equations (SFSDEs). Borrowing the heterogeneous multiscale idea, we propose an explicit multiscale Euler-Maruyama scheme suitable…

Numerical Analysis · Mathematics 2025-03-18 Yuanping Cui , Xiaoyue Li , Xuerong Mao

We discuss numerical approximation methods for Random Time Change equations which possess a deterministic drift part and jump with state-dependent rates. It is first established that solutions to such equations are versions of certain…

Probability · Mathematics 2013-10-03 Martin G. Riedler , Girolama Notarangelo

The aim of this paper is to investigate strong convergence of modified truncated Euler-Maruyama method for neutral stochastic differential delay equations introduced in Lan (2018). Strong convergence rates of the given numerical scheme to…

Probability · Mathematics 2018-07-25 Guangqiang Lan , Qiushi Wang

We investigate the strong approximation of stochastic differential equations whose drift is square-integrable in time and Dini continuous in space, while the diffusion coefficient is non-constant and uniformly elliptic. Using a refined…

Probability · Mathematics 2026-02-16 Jinlong Wei , Junhao Hu , Guangying Lv , Chenggui Yuan

The strong convergence of Euler approximations of stochastic delay differential equations is proved under general conditions. The assumptions on drift and diffusion coefficients have been relaxed to include polynomial growth and only…

Probability · Mathematics 2013-03-07 Chaman Kumar , Sotirios Sabanis

Motivated by truncated EM method introduced by Mao (2015), a new explicit numerical method named modified truncated Euler-Maruyama method is developed in this paper. Strong convergence rates of the given numerical scheme to the exact…

Probability · Mathematics 2017-01-18 Guangqiang Lan , Fang Xia

In this paper, we consider stochastic differential equations whose drift coefficient is superlinearly growing and piece-wise continuous, and whose diffusion coefficient is superlinearly growing and locally H\"older continuous. We first…

Probability · Mathematics 2023-05-15 Minh-Thang Do , Hoang-Long Ngo , Nhat-An Pho

In this paper, we derive error estimates of the backward Euler-Maruyama method applied to multi-valued stochastic differential equations. An important example of such an equation is a stochastic gradient flow whose associated potential is…

Numerical Analysis · Mathematics 2022-05-10 Monika Eisenmann , Mihály Kovács , Raphael Kruse , Stig Larsson

Most existing literature focuses on pointwise convergence (i.e., convergence at a fixed time point) of numerical solutions for Stochastic functional differential equations (SFDEs). In contrast, this paper investigates the strong segment…

Numerical Analysis · Mathematics 2026-04-24 Shounian Deng , Weiyin Fei , Banban Shi

In this article we establish exponential moment bounds, moment bounds in fractional order smoothness spaces, a uniform H\"older continuity in time, and strong convergence rates for a class of fully discrete exponential Euler-type numerical…

Probability · Mathematics 2021-11-02 Arnulf Jentzen , Felix Lindner , Primož Pušnik
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