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Related papers: Stopped Brownian-increment tamed Euler method

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We address the weak numerical solution of stochastic differential equations driven by independent Brownian motions (SDEs for short). This paper develops a new methodology to design adaptive strategies for determining automatically the…

Probability · Mathematics 2023-02-10 Carlos M. Mora , Juan Carlos Jimenez , Monica Selva

We describe an Euler scheme to approximate solutions of L\'evy driven Stochastic Differential Equations (SDE) where the grid points are random and given by the arrival times of a Poisson process. This result extends a previous work of the…

Probability · Mathematics 2013-09-10 Albert Ferreiro-Castilla , Andreas E Kyprianou , Robert Scheichl

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

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

This paper investigates the strong convergence properties of two Euler-type methods for a class of time-changed stochastic differential equations (TCSDEs) with super-linearly growing drift and diffusion coefficients. Building upon existing…

Numerical Analysis · Mathematics 2026-01-16 Shuai Wang , Yuanling Niu , Ying Zhang

In this paper we study strong approximation of the solution of a scalar stochastic differential equation (SDE) at the final time in the case when the drift coefficient may have discontinuities in space. Recently it has been shown in…

Probability · Mathematics 2019-04-22 Thomas Müller-Gronbach , Larisa Yaroslavtseva

It is well known that the Euler method for a random ordinary differential equation $\mathrm{d}X_t/\mathrm{d}t = f(t, X_t, Y_t)$ driven by a stochastic process $\{Y_t\}_t$ with $\theta$-H\"older sample paths is estimated to be of strong…

Probability · Mathematics 2025-10-21 Peter E. Kloeden , Ricardo M. S. Rosa

We introduce a predictor-corrector discretisation scheme for the numerical integration of a class of stochastic differential equations and prove that it converges with weak order 1.0. The key feature of the new scheme is that it builds up…

Computation · Statistics 2024-02-01 Deniz Akyildiz , Dan Crisan , Joaquin Miguez

This paper focuses on the strong convergence rate of both Runge--Kutta methods and simplified step-$N$ Euler schemes for stochastic differential equations driven by multi-dimensional fractional Brownian motions with $H\in(\frac12,1)$. Based…

Numerical Analysis · Mathematics 2021-04-23 Jialin Hong , Chuying Huang , Xu Wang

In this paper we investigate explicit numerical approximations for stochastic differential delay equations (SDDEs) under a local Lipschitz condition by employing the adaptive Euler-Maruyama (EM) method. Working in both finite and infinite…

Probability · Mathematics 2023-08-31 Ulises Botija-Munoz , Chenggui Yuan

Backward stochastic differential equations (BSDEs) appear in numeruous applications. Classical approximation methods suffer from the curse of dimensionality and deep learning-based approximation methods are not known to converge to the BSDE…

Probability · Mathematics 2022-04-20 Martin Hutzenthaler , Tuan Anh Nguyen

In this paper, employing the weak convergence method, based on a variational representation for expected values of positive functionals of a Brownian motion, we investigate moderate deviation %(CLT for abbreviation) for a class of…

Probability · Mathematics 2018-06-29 Yongqiang Suo , Jin Tao , Wei Zhang

We investigate synchronization by noise for stochastic differential equations (SDEs) driven by a fractional Brownian motion (fbm) with Hurst index $H\in(0,1)$. Provided that the SDE has a negative top Lyapunov exponent, we show that a weak…

Probability · Mathematics 2026-03-16 Alexandra Blessing , Mazyar Ghani Varzaneh

We study pathwise approximation of scalar stochastic differential equations at a single time point or globally in time by means of methods that are based on finitely many observations of the driving Brownian motion. We prove lower error…

Numerical Analysis · Mathematics 2017-10-25 Mario Hefter , André Herzwurm , Thomas Müller-Gronbach

In this paper, we present a discrete-type approximation scheme to solve continuous-time optimal stopping problems based on fully non-Markovian continuous processes adapted to the Brownian motion filtration. The approximations satisfy…

Probability · Mathematics 2019-06-24 Dorival Leão , Alberto Ohashi , Francesco Russo

We develop and analyze a general class of Euler-type numerical schemes for Levy-driven McKean-Vlasov stochastic differential equations (SDEs), where the drift, diffusion and jump coefficients grow super-linearly in the state variable. These…

Numerical Analysis · Mathematics 2025-09-12 Jingtao Zhu , Yuying Zhao , Siqing Gan

Numerical methods for SDEs with irregular coefficients are intensively studied in the literature, with different types of irregularities usually being attacked separately. In this paper we combine two different types of irregularities:…

Numerical Analysis · Mathematics 2024-01-12 Kathrin Spendier , Michaela Szölgyenyi

The aim of this paper is to investigate strong convergence of modified truncated Euler-Maruyama method for neutral stochastic differential delay equations introduced in Lan (2018). Strong convergence rates of the given numerical scheme to…

Probability · Mathematics 2018-07-25 Guangqiang Lan , Qiushi Wang

This article offers sharp spatial and temporal mean-square regularity results for a class of semi-linear parabolic stochastic partial differential equations (SPDEs) driven by infinite dimensional fractional Brownian motion with the Hurst…

Numerical Analysis · Mathematics 2020-08-04 Xiaojie Wang , Ruisheng Qi , Fengze Jiang

We introduce a new approach for designing numerical schemes for stochastic differential equations (SDEs). The approach, which we have called direction and norm decomposition method, proposes to approximate the required solution $X_t$ by…

Numerical Analysis · Mathematics 2017-02-21 C. M. Mora , H. A. Mardones , J. C. Jimenez , M. Selva , R. Biscay
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