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This paper focuses on the strong convergence of the truncated $\theta$-Milstein method for a class of nonautonomous stochastic differential delay equations whose drift and diffusion coefficients can grow polynomially. The convergence rate,…

Numerical Analysis · Mathematics 2021-12-28 Shuaibin Gao , Junhao Hu , Jie He , Qian Guo

This work presents a randomized-tamed Milstein scheme for stochastic differential equations whose drift coefficient exhibits superlinear growth in the state variable and limited temporal regularity, quantified by $\beta$-H\"older continuity…

Numerical Analysis · Mathematics 2026-01-15 Sani Biswas

This article studies the temporal approximation of hyperbolic semilinear stochastic evolution equations with multiplicative Gaussian noise by Milstein-type schemes. We take the term hyperbolic to mean that the leading operator generates a…

Numerical Analysis · Mathematics 2026-02-03 Felix Kastner , Katharina Klioba

We consider a higher-order Milstein scheme for stochastic partial differential equations with trace class noise which fulfill a certain commutativity condition. A novel technique to generally improve the order of convergence of Taylor…

Numerical Analysis · Mathematics 2018-08-15 Claudine Leonhard , Andreas Rößler

A convergence theorem for the continuous weak approximation of the solution of stochastic differential equations by general one step methods is proved, which is an extension of a theorem due to Milstein. As an application, uniform second…

Numerical Analysis · Mathematics 2013-03-19 Kristian Debrabant , Andreas Rößler

In this paper, we develop a new explicit scheme called modified truncated Milstein method which is motivated by truncated Milstein method proposed by Guo (2018) and modified truncated Euler-Maruyama method introduced by Lan (2018). We…

Numerical Analysis · Mathematics 2022-09-27 Yu Jiang , Guangqiang Lan

In this paper we study the rate of convergence of a symmetrized version of the Milstein scheme applied to the solution of the one dimensional SDE $$X_t = x_0 + \int_{0}^t{b(X_s)ds}+\int_{0}^t{\sigma |X_s|^\alpha dW_s}, \;x_0>0,\;\sigma>0,\;…

Probability · Mathematics 2018-11-28 Mireille Bossy , Hector Olivero Quinteros

In order to approximate solutions of stochastic partial differential equations (SPDEs) that do not possess commutative noise, one has to simulate the involved iterated stochastic integrals. Recently, two approximation methods for iterated…

Probability · Mathematics 2019-10-09 Claudine von Hallern , Andreas Rößler

The present article aims to design and analyze efficient first-order strong schemes for a generalized A\"{i}t-Sahalia type model arising in mathematical finance and evolving in a positive domain $(0, \infty)$, which possesses a diffusion…

Numerical Analysis · Mathematics 2024-07-15 Yingsong Jiang , Ruishu Liu , Xiaojie Wang , Jinghua Zhuo

In this work, an adaptive time-stepping Milstein method is constructed for stochastic differential equations with piecewise continuous arguments (SDEPCAs), where the drift is one-sided Lipschitz continuous and the diffusion does not impose…

Numerical Analysis · Mathematics 2025-02-25 Yuhang Zhang , Minghui Song , Jiaqi Zhu

For stochastic differential equations (SDEs) with a superlinearly growing and globally one-sided Lipschitz continuous drift coefficient, the classical explicit Euler scheme fails to converge strongly to the exact solution. Recently, an…

Numerical Analysis · Mathematics 2014-08-26 Xiaojie Wang , Siqing Gan

The coefficients of the stochastic differential equations with Markovian switching (SDEwMS) additionally depend on a Markov chain and there is no notion of differentiating such functions with respect to the Markov chain. In particular, this…

Probability · Mathematics 2022-11-22 Tejinder Kumar , Chaman Kumar

The aim of this note is to propose a novel numerical scheme for drift-less one dimensional stochastic differential equations of It\^o's type driven by standard Brownian motion. Our approximation method is equivalent to the well known…

Probability · Mathematics 2024-07-24 Alberto Lanconelli , Berk Tan Perçin

Motivated by weak convergence results in the paper of Takahashi and Yoshida (2005), we show strong convergence for an accelerated Euler-Maruyama scheme applied to perturbed stochastic differential equations. The Milstein scheme with the…

Computational Finance · Quantitative Finance 2013-12-02 Hideyuki Tanaka , Toshihiro Yamada

In this paper, we derive fully implementable first order time-stepping schemes for McKean--Vlasov stochastic differential equations (McKean--Vlasov SDEs), allowing for a drift term with super-linear growth in the state component. We propose…

Probability · Mathematics 2021-04-28 Jianhai Bao , Christoph Reisinger , Panpan Ren , Wolfgang Stockinger

We consider the Euler-Maruyama approximation for multi-dimensional stochastic differential equations with irregular coefficients. We provide the rate of strong convergence where the possibly discontinuous drift coefficient satisfies a…

Probability · Mathematics 2014-04-11 Hoang-Long Ngo , Dai Taguchi

This paper examines convergence and stability of the two classes of theta-Milstein schemes for stochastic differential equations (SDEs) with non-global Lipschitz continuous coefficients: the split-step theta-Milstein (SSTM) scheme and the…

Numerical Analysis · Mathematics 2015-01-16 Xiaofeng Zong , Fuke Wu , Guiping Xu

In this paper, we first establish well-posedness of McKean-Vlasov stochastic differential equations (McKean-Vlasov SDEs) with common noise, possibly with coefficients having super-linear growth in the state variable. Second, we present…

Probability · Mathematics 2020-06-02 Chaman Kumar , Neelima , Christoph Reisinger , Wolfgang Stockinger

We consider split-step Milstein methods for the solution of stiff stochastic differential equations with an emphasis on systems driven by multi-channel noise. We show their strong order of convergence and investigate mean-square stability…

Numerical Analysis · Mathematics 2014-11-27 V. Reshniak , A. Q. M. Khaliq , D. A. Voss , G. Zhang

Stochastic differential equations (SDEs) offer powerful and accessible mathematical models for capturing both deterministic and probabilistic aspects of dynamic behavior across a wide range of physical, financial, and social systems.…

Statistics Theory · Mathematics 2026-02-17 Paromita Banerjee , Anirban Mondal