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

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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.
Original languageSpanish (Mexico)
Pages (from-to)408
Number of pages423
JournalJournal of Computational and Applied Mathematics
StateAccepted/In press - Jan 2017

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