On sub-polynomial lower error bounds for quadrature of SDEs with bounded smooth coefficients

ABSTRACTIn recent work of Hairer, Hutzenthaler and Jentzen, [11], a stochastic differential equation (SDE) with infinitely differentiable andbounded coefficients was constructed such that the Monte Carlo Euler method for approximation of the expected value of the first component of the solution at the final time converges but fails to achieve a mean square error of a polynomial rate. In this article, we show that this type of bad performance for quadrature of SDEs with infinitely differentiable and bounded coefficients is not a shortcoming of the Euler scheme in particular but can be observed in a worst case sense for every approximation method that is based on finitely many function values of the coefficients of the SDE. Even worse we show that for any sequence of Monte Carlo methods based on finitely many sequential evaluations of the coefficients and all their partial derivatives and for every arbitrarily slow convergence speed there exists a sequence of SDEs with infinitely differentiable and bounded ...