A Control Variate Method for Weak Approximation of SDEs via Discretization of Numerical Error of Asymptotic Expansion

The paper shows a new weak approximation method for stochastic differential equations as a generalization and an extension of Heath-Platen's scheme for multidimensional diffusion processes. We reformulate the Heath-Platen estimator from the viewpoint of asymptotic expansion. The proposed scheme is implemented by a Monte Carlo method and its variance is much reduced by the asymptotic expansion which works as a kind of control variate. Numerical examples for the local stochastic volatility model are shown to confirm the efficiency of the method