An adaptive Euler-Maruyama scheme for stochastic differential equations with discontinuous drift and its convergence analysis
arXiv:1802.04521 · doi:10.1137/18M1170017
Abstract
We study the strong approximation of stochastic differential equations with discontinuous drift coefficients and (possibly) degenerate diffusion coefficients. To account for the discontinuity of the drift coefficient we construct an adaptive step sizing strategy for the explicit Euler-Maruyama scheme. As a result, we obtain a numerical method which has -- up to logarithmic terms -- strong convergence order with respect to the average computational cost. We support our theoretical findings with several numerical examples.
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Cited by in corpus (10)
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- Sharp lower error bounds for strong approximation of SDEs with piecewise Lipschitz continuous drift coefficient
- Error estimates of the backward Euler-Maruyama method for multi-valued stochastic differential equations
- Bicausal optimal transport for SDEs with irregular coefficients
- Convergence rate of numerical scheme for SDEs with a distributional drift in Besov space