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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 the ergodic properties of a class of controlled stochastic differential equations (SDEs) driven by $\alpha$-stable processes which arise as the limiting equations of multiclass queueing models in the Halfin-Whitt regime that have…

Probability · Mathematics 2019-07-22 Ari Arapostathis , Hassan Hmedi , Guodong Pang , Nikola Sandrić

In the past decade, an intensive study of strong approximation of stochastic differential equations (SDEs) with a drift coefficient that has discontinuities in space has begun. In the majority of these results it is assumed that the drift…

Probability · Mathematics 2020-10-05 Thomas Müller-Gronbach , Larisa Yaroslavtseva

This paper explores the rates of convergence of solutions for multivariate stochastic differential equations (SDEs) driven by L\'evy processes within the small-time stable domain of attraction (DoA). Explicit bounds are derived for the…

Probability · Mathematics 2025-09-17 Jorge González Cázares , David Kramer-Bang

In recent work of Hairer, Hutzenthaler and Jentzen, see [9], a stochastic differential equation (SDE) with infinitely often differentiable and bounded coefficients was constructed such that the Monte Carlo Euler method for approximation of…

Numerical Analysis · Mathematics 2016-03-30 Thomas Müller-Gronbach , Larisa Yaroslavtseva

We consider a process given as the solution of a stochastic differential equation with irregular, path dependent and time-inhomogeneous drift coefficient and additive noise. Explicit and optimal bounds for the Lebesgue density of that…

Probability · Mathematics 2015-08-04 David Baños , Paul Krühner

In this paper, we analyze the drift-implicit (or backward) Euler numerical scheme for a class of stochastic differential equations with unbounded drift driven by an arbitrary $\lambda$-H\"older continuous process, $\lambda\in(0,1)$. We…

Probability · Mathematics 2022-04-20 Giulia Di Nunno , Yuliya Mishura , Anton Yurchenko-Tytarenko

In this paper, we are concerned with convergence rate of Euler-Maruyama scheme for stochastic differential equations with rough coefficients. The key contributions lie in (i), by means of regularity of non-degenerate Kolmogrov equation, we…

Probability · Mathematics 2016-09-21 Jianhai Bao , Xing Huang , Chenggui Yuan

We study the strong convergence order of the Euler-Maruyama scheme for scalar stochastic differential equations with additive noise and irregular drift. We provide a general framework for the error analysis by reducing it to a weighted…

Probability · Mathematics 2020-11-03 Andreas Neuenkirch , Michaela Szölgyenyi

In this paper we investigate the convergence rate of Euler-Maruyama scheme for a class of stochastic differential delay equations, where the corresponding coefficients may be highly nonlinear with respect to the delay variables. In…

Probability · Mathematics 2011-11-18 Jianhai Bao , Chenggui Yuan

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 recent years, an intensive study of strong approximation of stochastic differential equations (SDEs) with a drift coefficient that may have discontinuities in space has begun. In many of these results it is assumed that the drift…

Probability · Mathematics 2021-03-01 Larisa Yaroslavtseva

Our subject of study is strong approximation of stochastic differential equations (SDEs) with respect to the supremum error criterion, and we seek approximations that are strongly asymptotically optimal in specific classes of…

Numerical Analysis · Mathematics 2020-07-17 Simon Hatzesberger

Recently, extracting data-driven governing laws of dynamical systems through deep learning frameworks has gained a lot of attention in various fields. Moreover, a growing amount of research work tends to transfer deterministic dynamical…

Machine Learning · Statistics 2022-07-05 Cheng Fang , Yubin Lu , Ting Gao , Jinqiao Duan

In the present work, we delve into further study of numerical approximations of SDEs with non-globally monotone coefficients. We design and analyze a new family of stopped increment-tamed time discretization schemes of Euler, Milstein and…

Numerical Analysis · Mathematics 2024-10-08 Lei Dai , Xiaojie Wang

In this paper, we show the strong well-posedness of Mckean-Vlasov SDEs with non-Lipschitz coefficients. Moreover, propagation of chaos and the convergence rate for Euler's scheme of Mckean-Vlasov SDEs are also obtained.

Probability · Mathematics 2022-02-18 Zhen Wang , Jie Ren , Yu Miao

This article proposes and analyzes explicit and easily implementable temporal numerical approximation schemes for additive noise-driven stochastic partial differential equations (SPDEs) with polynomial nonlinearities such as, e.g.,…

Probability · Mathematics 2021-11-02 Sebastian Becker , Arnulf Jentzen

We consider an SDE in R^m of the type dX(t)=a(X(t))dt+dU(t) with a L\'evy process U and study the problem for the distribution of a solution to be regular in various senses. We do not impose any specific conditions on the L\'evy measure of…

Probability · Mathematics 2007-05-23 Alexey Kulik

By establishing the regularity estimates for nonlocal Stein/Poisson equations under $\gamma$-order H\"older and dissipative conditions on the coefficients, we derive the $W_{\bf d}$-convergence rate for the Euler-Maruyama schemes applied to…

Probability · Mathematics 2024-11-18 Peng Chen , Lihu Xu , Xiaolong Zhang , Xicheng Zhang

This paper studies the numerical methods to approximate the solutions for a sort of McKean-Vlasov neutral stochastic differential delay equations (MV-NSDDEs) that the growth of the drift coefficients is super-linear. First, We obtain that…

Probability · Mathematics 2022-11-04 Yuanping Cui , Xiaoyue Li , Yi Liu , Chenggui Yuan