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This paper introduces a randomized tamed Euler scheme tailored for L\'evy-driven stochastic differential equations (SDEs) with superlinear random coefficients and Carath\'eodory-type drift. Under assumptions that allow for time-irregular…

Numerical Analysis · Mathematics 2025-10-22 Sani Biswas , Joaquin Fontbona

We extend the taming techniques for explicit Euler approximations of stochastic differential equations (SDEs) driven by L\'evy noise with super-linearly growing drift coefficients. Strong convergence results are presented for the case of…

Probability · Mathematics 2015-01-23 Konstantinos Dareiotis , Chaman Kumar , Sotirios Sabanis

In this article we propose a new explicit Euler-type approximation method for stochastic differential equations (SDEs). In this method, Brownian increments in the recursion of the Euler method are replaced by suitable bounded functions of…

Probability · Mathematics 2022-04-27 Martin Hutzenthaler , Kai Kisker

In traditional work on numerical schemes for solving stochastic differential equations (SDEs), it is usually assumed that the coefficients are globally Lipschitz. This assumption has been used to establish a powerful analysis of the…

Probability · Mathematics 2017-09-15 Philip Protter , Lisha Qiu , Jaime San Martin

In this paper, we investigate the asymptotic distribution of the normalized error for the Mittag--Leffler Euler (MLE) method applied to a class of multidimensional fractional stochastic differential equations. These equations are…

Numerical Analysis · Mathematics 2026-03-24 Xinjie Dai , Baiping Zhang , Diancong Jin

Over the last few decades, the numerical methods for stochastic differential delay equations (SDDEs) have been investigated and developed by many scholars. Nevertheless, there is still little work to be completed. By virtue of the novel…

Numerical Analysis · Mathematics 2022-09-21 Zhuoqi Liu , Qian Guo , Shuaibin Gao

We deduce the asymptotic error distribution of the Euler method for the nonlinear filtering problem with continuous-time observations. Previous works by several authors have shown that the error structure of the method is characterized by…

Probability · Mathematics 2018-09-10 Teppei Ogihara , Hideyuki Tanaka

In this paper, enlightened by the asymptotic expansion methodology developed by Li(2013b) and Li and Chen (2016), we propose a Taylor-type approximation for the transition densities of the stochastic differential equations (SDEs) driven by…

Computational Finance · Quantitative Finance 2020-03-16 Fan Jiang , Xin Zang , Jingping Yang

We consider the explicit numerical approximations of stochastic differential equations (SDEs) driven by Brownian process and Poisson jump. It is well known that under non-global Lipschitz condition, Euler Explicit method fails to converge…

Numerical Analysis · Mathematics 2018-02-21 Antoine Tambue , Jean Daniel Mukam

In the present article we study strong approximation of solutions of scalar stochastic differential equations (SDEs) with bounded and $\alpha$-H\"older continuous drift coefficient and constant diffusion coefficient at time point $1$.…

Probability · Mathematics 2025-04-30 Simon Ellinger , Thomas Müller-Gronbach , Larisa Yaroslavtseva

We design an energy-stable and asymptotic-preserving finite volume scheme for the compressible Euler system. Using the relative energy framework, we establish rigorous error estimates that yield convergence of the numerical solutions in two…

Numerical Analysis · Mathematics 2026-03-31 Megala Anandan , K. R. Arun , Amogh Krishnamurthy , Mária Lukáčová-Medvid'ová

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

This paper deals with the backward Euler method applied to semilinear parabolic stochastic partial differential equations (SPDEs) driven by additive noise. The SPDE is discretized in space by the finite element method and in time by the…

Numerical Analysis · Mathematics 2020-01-01 Jean Daniel Mukam , Antoine Tambue

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

In recent years tamed schemes have become an important technique for simulating SDEs and SPDEs whose continuous coefficients display superlinear growth. The taming method, which involves curbing the growth of the coefficients as a function…

Probability · Mathematics 2022-11-23 Tim Johnston , Sotirios Sabanis

As a well-known fact, the classical Euler scheme works merely for SDEs with coefficients of linear growth. In this paper, we study a general framework of modified Euler schemes, which is applicable to SDEs with super-linear drifts and…

Probability · Mathematics 2024-12-30 Jianhai Bao , Mateusz B. Majka , Jian Wang

We study McKean--Vlasov Stochastic Differential Equations (MV-SDEs) whose drift and diffusion coefficients are of superlinear growth in \textit{all} their variables thus also superlinear in the measure component (the meaning is specified in…

Probability · Mathematics 2025-10-21 Simran Soni , Neelima , Chaman Kumar , Goncalo dos Reis

This paper concerns the stability of analytical and numerical solutions of nonlinear stochastic delay differential equations (SDDEs). We derive sufficient conditions for the stability, contractivity and asymptotic contractivity in mean…

Numerical Analysis · Mathematics 2014-01-21 Siqing Gan , Aiguo Xiao , Desheng Wang

In this paper, we address the issue on non-asymptotic convergence bounds of Euler-type schemes associated with non-dissipative SDEs. On the one hand, for non-degenerate SDEs with super-linear drifts, we propose a novel modified Euler scheme…

Probability · Mathematics 2025-12-09 Jianhai Bao , Jiaqing Hao , Panpan Ren

We propose an algorithm for approximating the solution of a strongly oscillating SDE, that is, a system in which some ergodic state variables evolve quickly with respect to the other variables. The algorithm profits from homogenization…

Probability · Mathematics 2015-03-19 Camilo Andrés García Trillos