Optimal strong approximation of the one-dimensional squared Bessel process

DOI10.4310/CMS.2017.v15.n8.a2zbMath1453.65018arXiv1601.01455OpenAlexW2964129611MaRDI QIDQ1709650

Mario Hefter, André Herzwurm

Publication date: 6 April 2018

Published in: Communications in Mathematical Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1601.01455

zbMATH Keywords

adaptive algorithmstrong approximationreflected Brownian motionCox-Ingersoll-Ross process\(n\)-th minimal error

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Diffusion processes (60J60) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)

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An adaptive strong order 1 method for SDEs with discontinuous drift coefficient ⋮ A note on strong approximation of SDEs with smooth coefficients that have at most linearly growing derivatives ⋮ Strong convergence rates for Cox-Ingersoll-Ross processes -- full parameter range ⋮ Mean-reverting schemes for solving the CIR model ⋮ 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 ⋮ Adaptive quantile computation for Brownian bridge in change-point analysis

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