Strong convergence and temporal-spatial regularity for tamed Euler approximations of Lévy-driven SDEs
Provides rigorous convergence and regularity results for a new numerical scheme, benefiting researchers working on numerical methods for stochastic differential equations with irregular coefficients.
The paper introduces a novel tamed Euler scheme for Lévy-driven SDEs with superlinear coefficients, proving strong convergence and deriving temporal-spatial regularity estimates. Numerical experiments confirm the theoretical findings.
We study the temporal-spatial regularity properties of tamed Euler approximations for Lévy-driven SDEs with superlinearly growing drift and diffusion coefficients. We first introduce a novel tamed Euler-type scheme and establish its strong convergence. We then derive temporal-spatial regularity estimates with respect to the initial value, the initial time, and the evaluation time. In particular, we obtain a stability estimate for fixed step size and a corresponding continuity estimate in the vanishing step-size regime. Numerical experiments are presented to support the theoretical results.