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Consider the following stochastic differential equation (SDE) $$dX_t = b(t,X_{t-}) \, dt+ dL_t, \quad X_0 = x,$$ driven by a $d$-dimensional L\'evy process $(L_t)_{t \geq 0}$. We establish conditions on the L\'evy process and the drift…

Probability · Mathematics 2020-05-01 Franziska Kühn , René L. Schilling

The goal of this article is to establish a central limit theorem for the Euler-Maruyama scheme approximating multidimensional SDEs with elliptic Brownian diffusion, under very mild regularity requirements on the drift coefficients. When the…

Probability · Mathematics 2023-09-29 Konstantinos Dareiotis , Máté Gerencsér , Khoa Lê

In this paper, we are concerned with convergence rate of Euler-Maruyama scheme for stochastic differential equations with rough coefficients. The key contributions lie in (i), by means of regularity of non-degenerate Kolmogrov equation, we…

Probability · Mathematics 2016-09-21 Jianhai Bao , Xing Huang , Chenggui Yuan

In this paper, we study weak well-posedness of a McKean-Vlasov stochastic differential equations (SDEs) whose drift is density-dependent and whose diffusion is constant. The existence part is due to H\"older stability estimates of the…

Numerical Analysis · Mathematics 2025-11-20 Anh-Dung Le

We study the convergence of a generic tamed Euler-Maruyama (EM) scheme for the kinetic type stochastic differential equations (SDEs) (also known as second order SDEs) with singular coefficients in both weak and strong probabilistic senses.…

Probability · Mathematics 2024-09-10 Zimo Hao , Khoa Lê , Chengcheng Ling

In recent years, an intensive study of strong approximation of stochastic differential equations (SDEs) with a drift coefficient that may have discontinuities in space has begun. In many of these results it is assumed that the drift…

Probability · Mathematics 2021-03-01 Larisa Yaroslavtseva

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

In this paper we study the strong convergence for the Euler-Maruyama approximation of a class of stochastic differential equations whose both drift and diffusion coefficients are possibly discontinuous.

Probability · Mathematics 2016-09-02 Hoang-Long Ngo , Dai Taguchi

In this paper, we examine the performance of randomised Euler-Maruyama (EM) method for additive time-inhomogeneous SDEs with an irregular drift driven by symmetric $\alpha$-table process, $\alpha\in (1,2)$. In particular, the drift is…

Probability · Mathematics 2025-07-16 Jianhai Bao , Haitao Wang , Yue Wu , Danqi Zhuang

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 letter we prove existence and uniqueness of strong solutions to multi-dimensional SDEs with discontinuous drift and finite activity jumps.

Probability · Mathematics 2021-03-23 Paweł Przybyłowicz , Michaela Szölgyenyi , Fanhui Xu

The exponential stability of numerical methods to stochastic differential equations (SDEs) has been widely studied. In contrast, there are relatively few works on polynomial stability of numerical methods. In this letter, we address the…

Probability · Mathematics 2014-04-25 Mohammud Foondun , Wei Liu , Xuerong Mao

We consider SDEs with bounded and $\alpha$-H\"older continuous drift, with $\alpha \in (0,1)$, driven by multiplicative noise. We show that under sufficient conditions on the diffusion matrix, which guarantee the existence of a unique…

Probability · Mathematics 2022-06-28 Teodor Holland

This work establishes the weak convergence of Euler-Maruyama's approximation for stochastic differential equations (SDEs) with singular drifts under the integrability condition in lieu of the widely used growth condition. This method is…

Probability · Mathematics 2018-08-23 Jinghai Shao

For time-homogeneous stochastic differential equations (SDEs) it is enough to know that the coefficients are Lipschitz to conclude existence and uniqueness of a solution, as well as the existence of a strongly convergent numerical method…

Numerical Analysis · Mathematics 2018-12-04 Gunther Leobacher , Michaela Szölgyenyi

In this work, we present a general technique for establishing the strong convergence of numerical methods for stochastic delay differential equations (SDDEs) in the infinite horizon. This technique can also be extended to analyze certain…

Numerical Analysis · Mathematics 2025-05-21 Yudong Wang , Hongjiong Tian

This paper proposes an adaptive numerical method for stochastic delay differential equations (SDDEs) with a non-global Lipschitz drift term and a non-constant delay, building upon the work of Wei Fang and others. The method adapts the step…

Numerical Analysis · Mathematics 2024-07-02 Dongyang Liu , Minghui Song , Yuhang Zhang

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

In this paper, we consider a numerical approximation of the stochastic differential equation (SDE) $$X_{t}=x_{0}+ \int_{0}^{t} b(s, X_{s}) \mathrm{d}s + L_{t},~x_{0} \in \mathbb{R}^{d},~t \in [0,T],$$ where the drift coefficient $b:[0,T]…

Probability · Mathematics 2016-05-24 Olivier Menoukeu Pamen , Dai Taguchi

We study the strong $L^p$-convergence rates of the Euler-Maruyama method for stochastic differential equations driven by Brownian motion with low-regularity drift coefficients. Specifically, the drift is assumed to be in the…

Probability · Mathematics 2025-08-15 Jinlong Wei , Junhao Hu , Guangying Lv , Chenggui Yuan