Numerical methods for simulation of stochastic differential equations

72Citations
Citations of this article
73Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In this paper we are concerned with numerical methods to solve stochastic differential equations (SDEs), namely the Euler-Maruyama (EM) and Milstein methods. These methods are based on the truncated Ito-Taylor expansion. In our study we deal with a nonlinear SDE. We approximate to numerical solution using Monte Carlo simulation for each method. Also exact solution is obtained from Ito’s formula. To show the effectiveness of the numerical methods, approximation solutions are compared with exact solution for different sample paths. And finally the results of numerical experiments are supported with graphs and error tables.

Cite

CITATION STYLE

APA

Bayram, M., Partal, T., & Orucova Buyukoz, G. (2018). Numerical methods for simulation of stochastic differential equations. Advances in Difference Equations, 2018(1). https://doi.org/10.1186/s13662-018-1466-5

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free