Journal of Computational and Applied Mathematics2022,Vol.40618.DOI:10.1016/j.cam.2021.113924

A family of fully implicit strong Ito-Taylor numerical methods for stochastic differential equations

Liu, Kai Gu, Guiding
Journal of Computational and Applied Mathematics2022,Vol.40618.DOI:10.1016/j.cam.2021.113924

A family of fully implicit strong Ito-Taylor numerical methods for stochastic differential equations

Liu, Kai 1Gu, Guiding2
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作者信息

  • 1. Hunan Univ Technol & Business
  • 2. Shanghai Univ Finance & Econ
  • 折叠

Abstract

In this paper we design a family of fully implicit strong Ito-Taylor numerical methods for stochastic differential equations (SDE). These methods are based on the truncation of our general stochastic Ito-Taylor expansions, in which the truncation can be chosen to make our methods converge with high order. And by selecting the parameters in the methods, we can get methods with different stability. The mean-square (MS) stability of the second-order case is investigated. Numerical results are reported to show the convergence properties and the stability properties of our methods.(C) 2021 Elsevier B.V. All rights reserved.

Key words

Fully implicit/Numerical method/Stochastic differential equations/Stochastic Taylor expansions/Mean-square stability/MILSTEIN METHODS

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出版年

2022
Journal of Computational and Applied Mathematics

Journal of Computational and Applied Mathematics

EISCI
ISSN:0377-0427
参考文献量10
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