Weak convergence of balanced stochastic Runge-Kutta methods for stochastic differential equations

Anandaraman Rathinasamy, Kristian Debrabant*, Priya Nair

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

In this paper, weak convergence of balanced stochastic one-step methods and especially balanced stochastic Runge–Kutta (SRK) methods for Itô multidimensional stochastic differential equations is analyzed. Generalizing a corresponding result obtained by H. Schurz for the standard Euler method, it is shown that under certain conditions, balanced one-step methods preserve the weak convergence properties of their underlying methods. As an application, this allows to prove the weak convergence order of the balanced SRK methods presented in earlier work by A. Rathinasamy, P. Nair and D. Ahmadian.
Original languageEnglish
Article number2163546
JournalResearch in Mathematics
Volume10
Issue number1
ISSN2768-4830
DOIs
Publication statusPublished - 2023

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