General Full Implicit Strong Taylor Approximations for Stiff Stochastic Differential Equations

General Full Implicit Strong Taylor Approximations for Stiff Stochastic Differential Equations

Year:    2022

Author:    Kai Liu, Guiding Gu

Journal of Computational Mathematics, Vol. 40 (2022), Iss. 4 : pp. 541–569

Abstract

In this paper, we present the backward stochastic Taylor expansions for a Ito process, including backward Ito-Taylor expansions and backward Stratonovich-Taylor expansions. We construct the general full implicit strong Taylor approximations (including Ito-Taylor and Stratonovich-Taylor schemes) with implicitness in both the deterministic and the stochastic terms for the stiff stochastic differential equations (SSDE) by employing truncations of backward stochastic Taylor expansions. We demonstrate that these schemes will converge strongly with corresponding order $1,2,3,\ldots$ Mean-square stability  has been investigated for full implicit strong Stratonovich-Taylor scheme with order $2$, and it has larger mean-square stability region than the explicit and the semi-implicit strong Stratonovich-Taylor schemes with order $2$. We can improve the stability of simulations considerably without too much additional computational effort by using our full implicit schemes. The full implicit strong Taylor schemes allow a larger range of time step sizes than other schemes and are suitable for SSDE with stiffness on both the drift  and the diffusion terms. Our numerical experiment shows these points.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jcm.2011-m2019-0174

Journal of Computational Mathematics, Vol. 40 (2022), Iss. 4 : pp. 541–569

Published online:    2022-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    29

Keywords:    Stiff stochastic differential equations Approximations Backward stochastic Taylor expansions Full implicit Taylor methods.

Author Details

Kai Liu

Guiding Gu