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We study discrete-time simulation schemes for stochastic Volterra equations, namely the Euler and Milstein schemes, and the corresponding Multi-Level Monte-Carlo method. By using and adapting some results from Zhang [22], together with the…

Numerical Analysis · Mathematics 2022-03-08 Alexandre Richard , Xiaolu Tan , Fan Yang

Inspired by the truncated Euler-Maruyama method developed in Mao (J. Comput. Appl. Math. 2015), we propose the truncated Milstein method in this paper. The strong convergence rate is proved to be close to 1 for a class of highly non-linear…

Numerical Analysis · Mathematics 2017-07-07 Qian Guo , Wei Liu , Xuerong Mao , Rongxian Yue

This paper focuses on two variants of the Milstein scheme, namely the split-step backward Milstein method and a newly proposed projected Milstein scheme, applied to stochastic differential equations which satisfy a global monotonicity…

Numerical Analysis · Mathematics 2017-01-16 Wolf-Jürgen Beyn , Elena Isaak , Raphael Kruse

The multilevel Monte Carlo path simulation method introduced by Giles ({\it Operations Research}, 56(3):607-617, 2008) exploits strong convergence properties to improve the computational complexity by combining simulations with different…

Computational Finance · Quantitative Finance 2019-07-02 Michael B. Giles , Kristian Debrabant , Andreas Rößler

The Euler-Maruyama scheme is known to diverge strongly and numerically weakly when applied to nonlinear stochastic differential equations (SDEs) with superlinearly growing and globally one-sided Lipschitz continuous drift coefficients.…

Probability · Mathematics 2015-03-19 Martin Hutzenthaler , Arnulf Jentzen , Peter E. Kloeden

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

We consider the approximation of stochastic differential equations (SDEs) with non-Lipschitz drift or diffusion coefficients. We present a modified explicit Euler-Maruyama discretisation scheme that allows us to prove strong convergence,…

Computational Finance · Quantitative Finance 2016-04-12 Jean-Francois Chassagneux , Antoine Jacquier , Ivo Mihaylov

We study in this article the strong rate of convergence of the Euler-Maruyama scheme and associated with the jump-type equation introduced in Li and Mytnik. We obtain the strong rate of convergence under similar assumptions for strong…

Probability · Mathematics 2018-10-29 Libo Li , Dai Taguchi

We consider a class of stochastic path-dependent volatility models where the stochastic volatility, whose square follows the Cox-Ingersoll-Ross model, is multiplied by a (leverage) function of the spot price, its running maximum, and time.…

Computational Finance · Quantitative Finance 2018-10-09 Andrei Cozma , Christoph Reisinger

Motivated by truncated EM method introduced by Mao (2015), a new explicit numerical method named modified truncated Euler-Maruyama method is developed in this paper. Strong convergence rates of the given numerical scheme to the exact…

Probability · Mathematics 2017-01-18 Guangqiang Lan , Fang Xia

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 Euler-type framework with equidistant step sizes is proposed for a class of time-changed stochastic differential equations.We establish the strong convergence rate of the standard Euler--Maruyama method under the global Lipschitz…

Numerical Analysis · Mathematics 2026-03-12 Ruchun Zuo

This paper focuses on the numerical scheme for multiple-delay stochastic differential equations with partially H\"older continuous drifts and locally H\"older continuous diffusion coefficients. To handle with the superlinear terms in…

Numerical Analysis · Mathematics 2024-03-19 Zhuoqi Liu , Zhaohang Wang , Siying Sun , Shuaibin Gao

In this paper, we study the Euler--Maruyama scheme for a particle method to approximate the McKean--Vlasov dynamics of calibrated local-stochastic volatility (LSV) models. Given the open question of well-posedness of the original problem,…

Computational Finance · Quantitative Finance 2023-09-04 Christoph Reisinger , Maria Olympia Tsianni

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

This paper is concerned with the numerical approximation of stochastic ordinary differential equations, which satisfy a global monotonicity condition. This condition includes several equations with super-linearly growing drift and diffusion…

Numerical Analysis · Mathematics 2015-10-09 Wolf-Jürgen Beyn , Elena Isaak , Raphael Kruse

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

In this paper, we first establish the existence, uniqueness and H\"older continuity of the solution to stochastic Volterra integral equations with weakly singular kernels. Then, we propose a $\theta$-Euler-Maruyama scheme and a Milstein…

Numerical Analysis · Mathematics 2020-04-13 Min Li , Chengming Huang , Yaozhong Hu

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

We consider the problem of numerically estimating expectations of solutions to stochastic differential equations driven by Brownian motions in the commonly occurring small noise regime. We consider (i) standard Monte Carlo methods combined…

Numerical Analysis · Mathematics 2015-06-08 David F. Anderson , Desmond J. Higham , Yu Sun
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