A high-order recombination algorithm for weak approximation of stochastic differential equations

Fuente: arXiv
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Autori principali: Ninomiya, Syoiti, Shinozaki, Yuji
Natura: Preprint
Pubblicazione: 2025
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author Ninomiya, Syoiti
Shinozaki, Yuji
author_facet Ninomiya, Syoiti
Shinozaki, Yuji
contents This paper presents an algorithm for applying the high-order recombination method, originally introduced by Lyons and Litterer in ``High-order recombination and an application to cubature on Wiener space'' (Ann. Appl. Probab. 22(4):1301--1327, 2012), to practical problems in mathematical finance. A refined error analysis is provided, yielding a sharper condition for space partitioning. Based on this condition, a computationally feasible recursive partitioning algorithm is developed. Numerical examples are also included, demonstrating that the proposed algorithm effectively avoids the explosive growth in the cardinality of the support required to achieve high-order approximations.
format Preprint
id arxiv_https___arxiv_org_abs_2504_19717
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A high-order recombination algorithm for weak approximation of stochastic differential equations
Ninomiya, Syoiti
Shinozaki, Yuji
Probability
Computational Finance
91G60, 60H35, 65C20, 65C30, 65C05, 68U20, 62P05
This paper presents an algorithm for applying the high-order recombination method, originally introduced by Lyons and Litterer in ``High-order recombination and an application to cubature on Wiener space'' (Ann. Appl. Probab. 22(4):1301--1327, 2012), to practical problems in mathematical finance. A refined error analysis is provided, yielding a sharper condition for space partitioning. Based on this condition, a computationally feasible recursive partitioning algorithm is developed. Numerical examples are also included, demonstrating that the proposed algorithm effectively avoids the explosive growth in the cardinality of the support required to achieve high-order approximations.
title A high-order recombination algorithm for weak approximation of stochastic differential equations
topic Probability
Computational Finance
91G60, 60H35, 65C20, 65C30, 65C05, 68U20, 62P05
url https://arxiv.org/abs/2504.19717