An introduction to SDE simulation

Abstract

We outline the basic ideas and techniques underpinning the simulation of stochastic differential equations. In particular we focus on strong simulation and its context. We also provide illustratory examples and sample matlab algorithms for the reader to use and follow. Our target audience is advanced undergraduate and graduate students interested in learning about simulating stochastic differential equations. We try to address the FAQs we have encountered.

arXiv comment27 pages, 3 figures, review article

Cited by in corpus (4)

• Stochastic Runge-Kutta Software Package for Stochastic Differential Equations
• Adaptive time-stepping Monte Carlo integration of Coulomb collisions
• Noisy Recurrent Neural Networks
• Stochastic analysis & discrete quantum systems