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A Comparison of Higher-Order Weak Numerical Schemes for Stopped Stochastic Differential Equations

Part of: Stochastic processes Probability theory and stochastic processes Numerical analysis

Published online by Cambridge University Press:  31 August 2016

Francisco Bernal  and
Juan A. Acebrón
Francisco Bernal*
Affiliation:
INESC-ID\IST, TU Lisbon. Rua Alves Redol 9, 1000-029 Lisbon, Portugal Center for Mathematics and its Applications, Department of Mathematics, Instituto Superior Técnico. Av. Rovisco Pais 1049-001 Lisbon, Portugal
Juan A. Acebrón*
Affiliation:
INESC-ID\IST, TU Lisbon. Rua Alves Redol 9, 1000-029 Lisbon, Portugal ISCTE - Instituto Universitário de Lisboa Departamento de Ciências e Tecnologias de Informação. Av. das Forças Armadas 1649-026 Lisbon, Portugal
*
*Corresponding author. Email addresses:[email protected] (F. Bernal), [email protected] (J. A. Acebrón)
*Corresponding author. Email addresses:[email protected] (F. Bernal), [email protected] (J. A. Acebrón)
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Abstract

We review, implement, and compare numerical integration schemes for spatially bounded diffusions stopped at the boundary which possess a convergence rate of the discretization error with respect to the timestep h higher than . We address specific implementation issues of the most general-purpose of such schemes. They have been coded into a single Matlab program and compared, according to their accuracy and computational cost, on a wide range of problems in up to ℝ48. The paper is self-contained and the code will be made freely downloadable.

Keywords

Weak convergenceFeynman-Kacstochastic differential equationbounded diffusionfirst-exit problem

MSC classification

Secondary: 60G50: Sums of independent random variables; random walks 60-08: Computational methods (not classified at a more specific level) 65-02: Research exposition (monographs, survey articles)
Type
Research Article
Information
Communications in Computational Physics , Volume 20 , Issue 3 , September 2016 , pp. 703 - 732
Copyright
Copyright © Global-Science Press 2016 

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