On the Itô-Alekseev-Gröbner formula for stochastic differential equations

Fuente: arXiv
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Hauptverfasser: Hudde, Anselm, Hutzenthaler, Martin, Jentzen, Arnulf, Mazzonetto, Sara
Format: Preprint
Veröffentlicht: 2018
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author Hudde, Anselm
Hutzenthaler, Martin
Jentzen, Arnulf
Mazzonetto, Sara
author_facet Hudde, Anselm
Hutzenthaler, Martin
Jentzen, Arnulf
Mazzonetto, Sara
contents In this article we establish a new formula for the difference of a test function of the solution of a stochastic differential equation and of the test function of an Itô process. The introduced formula essentially generalizes both the classical Alekseev-Gröbner formula from the literature on deterministic differential equations as well as the classical Itô formula from stochastic analysis. The proposed Itô-Alekseev-Gröbner formula is a powerful tool for deriving strong approximation rates for perturbations and approximations of stochastic ordinary and partial differential equations.
format Preprint
id arxiv_https___arxiv_org_abs_1812_09857
institution arXiv
publishDate 2018
record_format arxiv
spellingShingle On the Itô-Alekseev-Gröbner formula for stochastic differential equations
Hudde, Anselm
Hutzenthaler, Martin
Jentzen, Arnulf
Mazzonetto, Sara
Probability
60H10
In this article we establish a new formula for the difference of a test function of the solution of a stochastic differential equation and of the test function of an Itô process. The introduced formula essentially generalizes both the classical Alekseev-Gröbner formula from the literature on deterministic differential equations as well as the classical Itô formula from stochastic analysis. The proposed Itô-Alekseev-Gröbner formula is a powerful tool for deriving strong approximation rates for perturbations and approximations of stochastic ordinary and partial differential equations.
title On the Itô-Alekseev-Gröbner formula for stochastic differential equations
topic Probability
60H10
url https://arxiv.org/abs/1812.09857