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We present an error analysis of weak convergence of one-step numerical schemes for stochastic differential equations (SDEs) with super-linearly growing coefficients. Following Milstein's weak error analysis on the one-step approximation of…

Numerical Analysis · Mathematics 2023-03-29 Xiaojie Wang , Yuying Zhao , Zhongqiang Zhang

We present an error analysis of weak convergence of one-step numerical schemes for stochastic differential equations (SDEs) with super-linearly growing coefficients. Following Milstein's weak error analysis on the one-step approximation of…

Numerical Analysis · Mathematics 2023-03-29 Xiaojie Wang , Yuying Zhao , Zhongqiang Zhang

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

We consider numerical approximations of stochastic differential equations by the Euler method. In the case where the SDE is elliptic or hypoelliptic, we show a weak backward error analysis result in the sense that the generator associated…

Numerical Analysis · Mathematics 2011-05-04 Arnaud Debussche , Erwan Faou

This paper establishes a discretization scheme for a large class of stochastic differential equations driven by a time-changed Brownian motion with drift, where the time change is given by a general inverse subordinator. The scheme involves…

Probability · Mathematics 2015-11-13 Ernest Jum , Kei Kobayashi

We construct a nonstandard finite difference numerical scheme to approximate stochastic differential equations (SDEs) using the idea of weighed step introduced by R.E. Mickens. We prove the strong convergence of our scheme under locally…

Numerical Analysis · Mathematics 2015-07-23 Frédéric Pierret

In this work, we investigate the existence and properties of Gaussian-like densities for weak solutions of multidimensional stochastic differential equations driven by a mixture of completely correlated fractional Brownian motions. We…

Probability · Mathematics 2025-03-06 Maximilian Buthenhoff , Ercan Sönmez

To obtain strong convergence rates of numerical schemes, an overwhelming majority of existing works impose a global monotonicity condition on coefficients of SDEs. Nevertheless, there are still many SDEs from applications that do not have…

Numerical Analysis · Mathematics 2025-04-03 Lei Dai , Xiaojie Wang

The convergence of the first order Euler scheme and an approximative variant thereof, along with convergence rates, are established for rough differential equations driven by c\`adl\`ag paths satisfying a suitable criterion, namely the…

Probability · Mathematics 2025-09-16 Andrew L. Allan , Anna P. Kwossek , Chong Liu , David J. Prömel

In this paper, we investigate stochastic differential equations(SDEs) driven by a class of supercritical $\alpha$-stable process(including the rotational symmetric $\alpha-$stable process) with drift $b$. The weak well-posedness is proved,…

Probability · Mathematics 2020-09-17 Guohuan Zhao

Many stochastic differential equations (SDEs) in the literature have a superlinearly growing nonlinearity in their drift or diffusion coefficient. Unfortunately, moments of the computationally efficient Euler-Maruyama approximation method…

Probability · Mathematics 2020-11-25 Martin Hutzenthaler , Arnulf Jentzen

In this paper, we consider a fundamental class of stochastic differential equations with time delays. Our aim is to investigate the weak convergence with respect to delay parameter of the solutions. Based on the techniques of Malliavin…

Probability · Mathematics 2021-09-07 T. C. Son , N. T. Dung , N. V. Tan , T. M. Cuong , H. T. P. Thao , P. D. Tung

Consider the following stochastic differential equation driven by multiplicative noise on $\mathbb{R}^d$ with a superlinearly growing drift coefficient, \begin{align*} \mathrm{d} X_t = b (X_t) \, \mathrm{d} t + \sigma (X_t) \, \mathrm{d}…

Probability · Mathematics 2025-05-07 Xiang Li , Yingjun Mo , Haoran Yang

Via constructing an asymptotic coupling by reflection, in this paper we establish uniform-in-time estimates on probability distances for mean-field type SDEs, where the drift terms under consideration are dissipative merely in the long…

Probability · Mathematics 2024-09-26 Jianhai Bao , Jiaqing Hao

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

Stochastic symmetries and related invariance properties of finite dimensional SDEs driven by general cadlag semimartingales taking values in Lie groups are defined and investigated. The considered set of SDEs, first introduced by S. Cohen,…

Probability · Mathematics 2020-08-04 Sergio Albeverio , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

In this paper, we use the truncated EM method to study the finite time strong convergence for the SDEs with Poisson jumps under the Khasminskii-type condition. We establish the finite time $ \mathcal L ^r (r \ge 2) $ convergence rate when…

Numerical Analysis · Mathematics 2018-05-30 Shounian Deng , Weiyin Fei , Wei Liu , Xuerong Mao

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

In this paper we introduce a transformation technique, which can on the one hand be used to prove existence and uniqueness for a class of SDEs with discontinuous drift coefficient. One the other hand we present a numerical method based on…

Probability · Mathematics 2016-08-03 Gunther Leobacher , Michaela Szölgyenyi

The backward Euler-Maruyama (BEM) method is employed to approximate the invariant measure of stochastic differential equations, where both the drift and the diffusion coefficient are allowed to grow super-linearly. The existence and…

Probability · Mathematics 2022-06-24 Wei Liu , Xuerong Mao , Yue Wu
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