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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

This work presents a randomized-tamed Milstein scheme for stochastic differential equations whose drift coefficient exhibits superlinear growth in the state variable and limited temporal regularity, quantified by $\beta$-H\"older continuity…

Numerical Analysis · Mathematics 2026-01-15 Sani Biswas

Strong convergence results on tamed Euler schemes, which approximate stochastic differential equations with superlinearly growing drift coefficients that are locally one-sided Lipschitz continuous, are presented in this article. The…

Probability · Mathematics 2013-06-17 Sotirios Sabanis

We study the strong approximation of the solutions to singular stochastic kinetic equations (also referred to as second-order SDEs) driven by $\alpha$-stable processes, using an Euler-type scheme inspired by [11]. For these equations, the…

Probability · Mathematics 2025-11-18 Chengcheng Ling

We study strong approximation of $d$-dimensional stochastic differential equations (SDEs) with a discontinuous drift coefficient. More precisely, we essentially assume that the drift coefficient is piecewise Lipschitz continuous with an…

Numerical Analysis · Mathematics 2025-04-03 Thomas Müller-Gronbach , Christopher Rauhögger , Larisa Yaroslavtseva

We utilize the weak convergence method to establish the Freidlin--Wentzell large deviations principle (LDP) for stochastic delay differential equations (SDDEs) with super-linearly growing coefficients, which covers a large class of cases…

Probability · Mathematics 2022-01-04 Diancong Jin , Ziheng Chen , Tau Zhou

We propose a new simple and explicit numerical scheme for time-homogeneous stochastic differential equations. The scheme is based on sampling increments at each time step from a skew-symmetric probability distribution, with the level of…

Probability · Mathematics 2025-07-08 Yuga Iguchi , Samuel Livingstone , Nikolas Nüsken , Giorgos Vasdekis , Rui-Yang Zhang

Recently a lot of effort has been invested to analyze the $L_p$-error of the Euler-Maruyama scheme in the case of stochastic differential equations (SDEs) with a drift coefficient that may have discontinuities in space. For scalar SDEs with…

Numerical Analysis · Mathematics 2018-09-25 Thomas Müller-Gronbach , Larisa Yaroslavtseva

We propose a new scheme for the long time approximation of a diffusion when the drift vector field is not globally Lipschitz. Under this assumption, regular explicit Euler scheme --with constant or decreasing step-- may explode and implicit…

Probability · Mathematics 2018-02-20 Vincent Lemaire

We study $\mathbb{R}^d$-valued mean field stochastic differential equations with a diffusion coefficient depending on the $L_p$-norm of the process in a discontinuous way. We show that under a strong drift there exists a unique global…

Probability · Mathematics 2023-09-06 Jani Nykänen

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

It is well known that for a stochastic differential equation driven by L\'evy noise, the temporal H\"older continuity in $L^p$ sense of the exact solution does not exceed $1/p$. This leads to that the $L^p$-strong convergence order of a…

Numerical Analysis · Mathematics 2024-12-10 Chuchu Chen , Tonghe Dang , Jialin Hong , Ziyi Lei

We are investigating the first strong convergence analysis of a numerical method for stochastic differential algebraic equations (SDAEs) under a non-global Lipschitz setting. It is well known that the explicit Euler scheme fails to converge…

Numerical Analysis · Mathematics 2025-09-12 Guy Tsafack , Antoine Tambue

An explicit Milstein-type scheme for stochastic differential equation with Markovian switching is derived and its strong convergence in $\mathcal{L}^2$-sense is established without using It\^o-Taylor expansion formula. Rate of strong…

Probability · Mathematics 2019-09-18 Chaman Kumar , Tejinder Kumar

We study the strong rate of convergence of the Euler--Maruyama scheme for a multidimensional stochastic differential equation (SDE) $$ dX_t = b(X_t) \, dt + dL_t, $$ with irregular $\beta$-H\"older drift, $\beta > 0$, driven by a L\'evy…

Probability · Mathematics 2024-01-12 Oleg Butkovsky , Konstantinos Dareiotis , Máté Gerencsér

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

A new explicit stochastic scheme of order 1 is proposed for solving commutative stochastic differential equations (SDEs) with non-globally Lipschitz continuous coefficients. The proposed method is a semi-tamed version of Milstein scheme to…

Numerical Analysis · Mathematics 2021-10-13 Yulong Liu , Yuanling Niu , Xiujun Cheng

A stencil-adaptive SBP-SAT finite difference scheme is shown to display superconvergent behavior. Applied to the linear advection equation, it has a convergence rate $\mathcal{O}(\Delta x^4)$ in contrast to a conventional scheme, which…

Numerical Analysis · Mathematics 2023-07-27 Viktor Linders , Mark Carpenter , Jan Nordström

In this paper, we propose and analyze an adaptive time-stepping fully discrete scheme which possesses the optimal strong convergence order for the stochastic nonlinear Schr\"odinger equation with multiplicative noise. Based on the splitting…

Numerical Analysis · Mathematics 2022-12-06 Chuchu Chen , Tonghe Dang , Jialin Hong

The rates of strong convergence for various approximation schemes are investigated for a class of stochastic differential equations (SDEs) which involve a random time change given by an inverse subordinator. SDEs to be considered are unique…

Probability · Mathematics 2021-03-29 Sixian Jin , Kei Kobayashi