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We study the traditional backward Euler method for $m$-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H > 1/2$ whose drift coefficient satisfies the one-sided Lipschitz condition.…

Numerical Analysis · Mathematics 2022-05-30 Hao Zhou , Yaozhong Hu , Yanghui Liu

In this article we propose a model for stochastic delay differential equation with jumps (SDDEJ) in a differentiable manifold $M$ endowed with a connection $\nabla$. In our model, the continuous part is driven by vector fields with a fixed…

Dynamical Systems · Mathematics 2015-03-20 Leandro Morgado , Paulo R. Ruffino

We study the long time behavior of isentropic compressible Euler equations with linear damping driven by a white-in-time noise, on a one-dimensional torus. We prove the existence of a statistically stationary solution in the class of weak…

Analysis of PDEs · Mathematics 2025-11-03 Jeffrey Kuan , Krutika Tawri , Konstantina Trivisa

This paper is devoted to the study of reflected Stochastic Differential Equations with jumps when the constraint is not on the paths of the solution but acts on the law of the solution. This type of reflected equations have been introduced…

Probability · Mathematics 2020-08-26 Philippe Briand , Abir Ghannoum , Céline Labart

In this paper, we consider the equivalence of the $p$th moment exponential stability for stochastic differential equations (SDEs), stochastic differential equations with piecewise continuous arguments (SDEPCAs) and the corresponding…

Numerical Analysis · Mathematics 2020-01-16 Minghui Song , Yidan Geng , Mingzhu Liu

We consider stochastic differential equations (SDEs) driven by small L\'evy noise with some unknown parameters, and propose a new type of least squares estimators based on discrete samples from the SDEs. To approximate the increments of a…

Statistics Theory · Mathematics 2022-07-11 Mitsuki Kobayashi , Yasutaka Shimizu

The approximation of invariant measures for nonlinear ergodic stochastic differential equations (SDEs) is a central problem in scientific computing, with important applications in stochastic sampling, physics, and ecology. We first propose…

Numerical Analysis · Mathematics 2025-11-18 Shan Huang , Xiaoyue Li

This paper introduces Magnus-based methods for solving stochastic delay-differential equations (SDDEs). We construct Magnus--Euler--Maruyama (MEM) and Magnus--Milstein (MM) schemes by combining stochastic Magnus integrators with Taylor…

Numerical Analysis · Mathematics 2025-06-23 Mitchell T. Griggs , Kevin Burrage , Pamela M. Burrage

In this paper, the truncated Euler-Maruyama (EM) method is employed together with the Multi-level Monte Carlo (MLMC) method to approximate the expectations of functions of solutions to stochastic differential equations (SDEs). The…

Numerical Analysis · Mathematics 2017-02-22 Qian Guo , Wei Liu , Xuerong Mao , Weijun Zhan

We introduce an explicit adaptive Milstein method for stochastic differential equations (SDEs) with no commutativity condition. The drift and diffusion are separately locally Lipschitz and together satisfy a monotone condition. This method…

Numerical Analysis · Mathematics 2022-11-22 Cónall Kelly , Gabriel Lord , Fandi Sun

We study the asymptotic stability of the semi-discrete (SD) numerical method for the approximation of stochastic differential equations. Recently, we examined the order of $\mathcal L^2$-convergence of the truncated SD method and showed…

Numerical Analysis · Mathematics 2020-08-10 Nikolaos Halidias , Ioannis S. Stamatiou

A class of Hamiltonian stochastic differential equations with multiplicative L\'{e}vy noise in the sense of Marcus, and the construction and numerical implementation methods of symplectic Euler scheme, are considered. A general symplectic…

Numerical Analysis · Mathematics 2020-10-16 Qingyi Zhan , Jinqiao Duan , Xiaofan Li , Yuhong Li

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

In this paper, we define a notion of second-order backward stochastic differential equations with jumps (2BSDEJs for short), which generalizes the continuous case considered by Soner, Touzi and Zhang [Probab. Theory Related Fields 153…

Probability · Mathematics 2015-09-10 Nabil Kazi-Tani , Dylan Possamaï , Chao Zhou

This paper aims to investigate the asymptotic error distribution of several numerical methods for stochastic partial differential equations (SPDEs) with multiplicative noise. Firstly, we give the limit distribution of the normalized error…

Numerical Analysis · Mathematics 2025-11-10 Jialin Hong , Diancong Jin , Xu Wang

Mean square exponential stability of $\theta$-EM and modified truncated Euler-Maruyama (MTEM) methods for stochastic differential delay equations (SDDEs) are investigated in this paper. We present new criterion of mean square exponential…

Numerical Analysis · Mathematics 2023-06-22 Guangqiang Lan , Qi Liu

Stochastic differential equations (SDEs) using jump-diffusion processes describe many natural phenomena at the microscopic level. Since they are commonly used to model economic and financial evolutions, the calibration and optimal control…

Optimization and Control · Mathematics 2025-05-08 Jan Bartsch , Alfio Borzi , Gabriele Ciaramella , Jan Reichle

We present a criterion for uniform in time convergence of the weak error of the Euler scheme for Stochastic Differential equations (SDEs). The criterion requires i) exponential decay in time of the space-derivatives of the semigroup…

Probability · Mathematics 2020-07-28 D. Crisan , P. Dobson , M. Ottobre

In this paper, we study analytical properties of the solutions to the generalised delay Ait-Sahalia-type interest rate model with Poisson-driven jump. Since this model does not have explicit solution, we employ several new truncated…

Risk Management · Quantitative Finance 2021-07-13 Emmanuel Coffie

This work introduces hybrid stochastic differential equations with memory (mH-SDEs), a new class of stochastic systems where transition rates depend on the joint history of both Euclidean and discrete components. This extends existing…

Probability · Mathematics 2026-03-30 Oscar Peralta