Efficient Approximation of SDEs Driven by Countably Dimensional Wiener Process and Poisson Random Measure

DOI10.1137/21M1442747zbMath1487.65011arXiv2108.02394OpenAlexW4226061793MaRDI QIDQ5072583

Paweł Przybyłowicz, Łukasz T. Stȩpień, Michał Sobieraj

Publication date: 29 April 2022

Published in: SIAM Journal on Numerical Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2108.02394

zbMATH Keywords

complexity analysisPoisson random measurestochastic differential equations with jumpslower error boundscountably dimensional Wiener processrandomized Euler algorithm

Mathematics Subject Classification ID

Analysis of algorithms and problem complexity (68Q25) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30) Complexity and performance of numerical algorithms (65Y20)

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Randomized Milstein algorithm for approximation of solutions of jump-diffusion SDEs ⋮ On approximation of solutions of stochastic delay differential equations via randomized Euler scheme

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