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In this paper the numerical approximation of stochastic differential equations satisfying a global monotonicity condition is studied. The strong rate of convergence with respect to the mean square norm is determined to be $\frac{1}{2}$ for…

Numerical Analysis · Mathematics 2017-09-01 Adam Andersson , Raphael Kruse

An implicit Euler--Maruyama method with non-uniform step-size applied to a class of stochastic partial differential equations is studied. A spectral method is used for the spatial discretization and the truncation of the Wiener process. A…

Numerical Analysis · Mathematics 2018-04-11 Yoshihito Kazashi

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

We consider a generic and explicit tamed Euler--Maruyama scheme for multidimensional time-inhomogeneous stochastic differential equations with multiplicative Brownian noise. The diffusive coefficient is uniformly elliptic, H\"older…

Probability · Mathematics 2025-02-03 Khoa Lê , Chengcheng Ling

We study the strong approximation of stochastic differential equations with discontinuous drift coefficients and (possibly) degenerate diffusion coefficients. To account for the discontinuity of the drift coefficient we construct an…

Numerical Analysis · Mathematics 2019-04-25 Andreas Neuenkirch , Michaela Szölgyenyi , Lukasz Szpruch

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 prove stability and convergence of a full discretization for a class of stochastic evolution equations with super-linearly growing operators appearing in the drift term. This is done using the recently developed tamed Euler method, which…

Probability · Mathematics 2015-08-14 István Gyöngy , Sotirios Sabanis , David Šiška

We establish a general theory of optimal strong error estimation for numerical approximations of a second-order parabolic stochastic partial differential equation with monotone drift driven by a multiplicative infinite-dimensional Wiener…

Numerical Analysis · Mathematics 2022-03-02 Zhihui Liu , Zhonghua Qiao

We survey recent developments in the field of complexity of pathwise approximation in $p$-th mean of the solution of a stochastic differential equation at the final time based on finitely many evaluations of the driving Brownian motion.…

Probability · Mathematics 2024-03-04 T. Müller-Gronbach , L. Yaroslavtseva

In this paper the numerical solution of non-autonomous semilinear stochastic evolution equations driven by an additive Wiener noise is investigated. We introduce a novel fully discrete numerical approximation that combines a standard…

Numerical Analysis · Mathematics 2019-07-01 Raphael Kruse , Yue Wu

This paper is concerned with fully discrete mixed finite element approximations of the time-dependent stochastic Stokes equations with multiplicative noise. A prototypical method, which comprises of the Euler-Maruyama scheme for time…

Numerical Analysis · Mathematics 2020-04-28 Xiaobing Feng , Hailong Qiu

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 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 are interested in the Euler-Maruyama discretization of a stochastic differential equation in dimension $d$ with constant diffusion coefficient and bounded measurable drift coefficient. In the scheme, a randomization of the time variable…

Probability · Mathematics 2020-11-13 Oumaima Bencheikh , Benjamin Jourdain

In this paper we study solutions to stochastic differential equations (SDEs) with discontinuous drift. We apply two approaches: The Euler-Maruyama method and the Fokker-Planck equation and show that a candidate density function based on the…

Systems and Control · Computer Science 2013-08-27 Maria Simonsen , John Leth , Henrik Schioler , Horia Cornean

In this paper, we establish the weak convergence rate of density-dependent stochastic differential equations with bounded drift driven by $\alpha$-stable processes with $\alpha\in(1,2)$. The well-posedness of these equations has been…

Probability · Mathematics 2024-06-03 Ke Song , Zimo Hao

In this paper, we introduce adaptive Euler-Maruyama schemes for McKean-Vlasov stochastic differential equations (SDEs) assuming only a standard monotonicity condition on the drift and diffusion coefficients but no global Lipschitz…

Numerical Analysis · Mathematics 2021-11-02 Christoph Reisinger , Wolfgang Stockinger

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

We introduce a class of adaptive timestepping strategies for stochastic differential equations with non-Lipschitz drift coefficients. These strategies work by controlling potential unbounded growth in solutions of a numerical scheme due to…

Numerical Analysis · Mathematics 2016-10-14 Cónall Kelly , Gabriel J. Lord

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
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