STOCHASTIC DIFFERENTIAL EQUATIONS SIMULATION OF EULER-MARUYAMA APPROXIMATION METHOD

Shaini, Bilall (2021) STOCHASTIC DIFFERENTIAL EQUATIONS SIMULATION OF EULER-MARUYAMA APPROXIMATION METHOD. Journal of Natural Sciences and Mathematics of UT, 6 (11-12). pp. 110-117. ISSN 2671-3039

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Abstract

This paper is an introduction and survey of numerical solution methods for stochastic differential equations. In mathematics and computational sciences, the Euler method is a first-order numerical procedure for solving ordinary differential equations (ODEs) with given initial value, in SDEs Euler approximations give one of the best results after working with an approximation method. Also, to the Stochastic Differential Equations (SDEs) one of the simplest time discrete approximation of an Ito process is the Euler approximation, or called the Euler-Maruyama approximation. We shall consider an Ito process satisfying the scalar of a SDE. And to illustrate various aspects of the simulation of a time discrete approximation of an Ito process we shall examine a simple example by using Excel Simulation and MathLab Simulation.

Item Type:	Article
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Engineering, Science and Mathematics > School of Mathematics
Depositing User:	Unnamed user with email zshi@unite.edu.mk
Date Deposited:	01 Sep 2021 11:31
Last Modified:	01 Sep 2021 11:31
URI:	http://eprints.unite.edu.mk/id/eprint/725

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