The linear Steklov method for SDEs with non-globally Lipschitz coefficients: Strong convergence and simulation

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摘要

We present an explicit numerical method for solving stochastic differential equations with non-globally Lipschitz coefficients. A linear version of the Steklov average under a split-step formulation supports our new solver. The linear Steklov method converges strongly with a standard one-half order. Also, we present numerical evidence that the explicit linear Steklov reproduces almost surely stability solutions with high-accuracy for diverse application models even for stochastic differential systems with super-linear diffusion coefficients.

论文关键词:Stochastic differential equations,Explicit methods,Strong convergence,Steklov average

论文评审过程:Received 6 October 2015, Revised 29 February 2016, Available online 2 May 2016, Version of Record 29 August 2016.

论文官网地址:https://doi.org/10.1016/j.cam.2016.04.011