Strong convergence of an explicit numerical approximation for n-dimensional superlinear SDEs with positive solutions
Cai, Yongmei and Guo, Qian and Mao, Xuerong (2024) Strong convergence of an explicit numerical approximation for n-dimensional superlinear SDEs with positive solutions. Mathematics and Computers in Simulation, 216. pp. 198-212. ISSN 0378-4754 (https://doi.org/10.1016/j.matcom.2023.09.011)
Preview |
Text.
Filename: Cai_etal_MCS_2024_Strong_convergence_of_an_explicit_numerical_approximation_for_n_dimensional_superlinear_SDEs_with_positive_solutions.pdf
Accepted Author Manuscript License: Download (1MB)| Preview |
Abstract
For a stochastic differential equation (SDE) with a unique positive solution, a rational numerical method is expected to be structure preserving. However, most existing methods are not, as far as we know. Some characteristics of the SDE models including the multi-dimension and super-linearity make it even more challenging. In this work, we fill the gap by proposing an explicit numerical method which is not only structure preserving but also cost effective. The strong convergence framework is set up by moment convergence analysis. We use the Lotka–Volterra system to elaborate our theory, nevertheless, the method works for a wide range of multi-dimensional superlinear SDE models.
ORCID iDs
Cai, Yongmei, Guo, Qian and Mao, Xuerong ORCID: https://orcid.org/0000-0002-6768-9864;-
-
Item type: Article ID code: 86966 Dates: DateEvent28 February 2024Published29 September 2023Published Online19 September 2023Accepted5 December 2022SubmittedNotes: Copyright © Elsevier Ltd. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ Subjects: Science > Mathematics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 16 Oct 2023 12:12 Last modified: 12 Dec 2024 15:02 URI: https://strathprints.strath.ac.uk/id/eprint/86966