Simultaneous time and chance discretization for stochastic differential equations

The paper deals with weak approximations of stochastic differential equations of Itô type, where convergence rates of the approximate solutions are shown using E¦|·¦|C[t0, T]P, p ϵ [2, ∞). The rates can also be interpreted as rates for the Lp Wasserstein metrics, p ϵ [1, ∞), between the distributions of exact and approximate solutions. The two approximation schemes considered are a combination of the time discretization methods of Euler and Milshtein with a chance discretization based on the invariance principle, and they work on a grid constructed to tune both discretizations.