Abstract

We present a fully probabilistic Euler scheme for the simulation of McKean-Vlasov Stochastic Differential Equations (MV-SDEs) with drifts of super-linear growth in the measure component (also in the spatial component, and random initial condition). We develop a split-step (implicit) scheme attaining an almost 1/2 root-mean-square error rate in stepsize and address a gap in the literature regarding efficient numerical methods and their convergence rate for this class of McKean Vlasov SDEs.