Convergence Rates of Split-Step Theta Methods for SDEs with Non-Globally Lipschitz Diffusion Coefficients

Convergence Rates of Split-Step Theta Methods for SDEs with Non-Globally Lipschitz Diffusion Coefficients

Year:    2023

Author:    Xiaojuan Wu, Siqing Gan

East Asian Journal on Applied Mathematics, Vol. 13 (2023), Iss. 1 : pp. 59–75

Abstract

The present work analyzes the mean-square approximation error of split-step theta methods in a non-globally Lipschitz regime. We show that under a coupled monotonicity condition and polynomial growth conditions, the considered methods with the parameters $θ ∈ [1/2, 1]$ have convergence rate of order $1/2.$ This covers a class of stochastic differential equations with super-linearly growing diffusion coefficients such as the popular $3/2$-model in finance. Numerical examples support the theoretical results.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/eajam.161121.090722

East Asian Journal on Applied Mathematics, Vol. 13 (2023), Iss. 1 : pp. 59–75

Published online:    2023-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    17

Keywords:    Stochastic differential equation non-globally Lipschitz coefficient split-step theta method strong convergence rate.

Author Details

Xiaojuan Wu

Siqing Gan

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    https://doi.org/10.1016/j.cnsns.2024.108372 [Citations: 0]