Euler-Maruyama schemes for stochastic differential equations driven by stable L\'evy processes with i. i. d. stable components

We study Euler-Maruyama numerical schemes of stochastic differential equations driven by stable L\'evy processes with i. i. d. stable components. We obtain a uniform-in-time approximation error in Wasserstein distance. Our approximation error has a linear dependence on the stepsize, which is expected to be tight, as can be seen from an explicit calculation for the case of an Ornstein-Uhlenbeck process. We also obtain a uniform-in-time approximation error when Pareto noises are used in the discretization scheme.