On stochastic differential equations with arbitrarily slow convergence rates for strong approximation in two space dimensions

DOI10.1098/rspa.2017.0104zbMath1404.60082arXiv1702.03229OpenAlexW2634856959WikidataQ52383404 ScholiaQ52383404MaRDI QIDQ4646879

Máté Gerencsér, Arnulf Jentzen, Diyora Salimova

Publication date: 28 December 2018

Published in: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.03229

zbMATH Keywords

stochastic differential equationlower error boundsslow convergence ratesmooth coefficients

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Ordinary differential equations and systems with randomness (34F05)

Related Items (6)

A note on strong approximation of SDEs with smooth coefficients that have at most linearly growing derivatives ⋮ On the performance of the Euler-Maruyama scheme for SDEs with discontinuous drift coefficient ⋮ On the regularisation of the noise for the Euler-Maruyama scheme with irregular drift ⋮ On arbitrarily slow convergence rates for strong numerical approximations of Cox-Ingersoll-Ross processes and squared Bessel processes ⋮ Lower error bounds for strong approximation of scalar SDEs with non-Lipschitzian coefficients ⋮ Strong convergence for explicit space-time discrete numerical approximation methods for stochastic Burgers equations

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