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An algorithmic introduction to numerical simulation of stochastic differential equations

Higham, D.J. (2001) An algorithmic introduction to numerical simulation of stochastic differential equations. SIAM Review, 43 (3). pp. 525-546. ISSN 0036-1445

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Abstract

A practical and accessible introduction to numerical methods for stochastic differential equations is given. The reader is assumed to be familiar with Euler's method for deterministic differential equations and to have at least an intuitive feel for the concept of a random variable; however, no knowledge of advanced probability theory or stochastic processes is assumed. The article is built around $10$ MATLAB programs, and the topics covered include stochastic integration, the Euler--Maruyama method, Milstein's method, strong and weak convergence, linear stability, and the stochastic chain rule.

Item type: Article
ID code: 174
Keywords: Euler--Maruyama method, MATLAB, Milstein method, Monte Carlo, stochastic simulation, strong and weak convergence, computer science, applied mathematics, Electronic computers. Computer science, Mathematics, Computational Mathematics, Theoretical Computer Science, Applied Mathematics
Subjects: Science > Mathematics > Electronic computers. Computer science
Science > Mathematics
Department: Faculty of Science > Mathematics and Statistics
Related URLs:
Depositing user: Ms Sarah Scott
Date Deposited: 03 Mar 2006
Last modified: 04 Sep 2014 10:22
URI: http://strathprints.strath.ac.uk/id/eprint/174

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