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