methods. Our methodology explores the idea that only a small part of the likelihood evaluation problem requires simulation. We …-off encountered by other sampling methods. An elaborate simulation study and an empirical application for U.S. stock returns reveal …

integrand are given by some stochastic differential equation. We also propose numerical simulation of stochastic differential … integrals terms at the initial time of the simulation along with the solution of the stochastic integrals which is found in … terms of Hermite polynomials and variance of the integrals. We apply the method of iterated integrals to simulation of …

Monte Carlo scheme which converges to the exact value. We manage to keep the simulation variance finite in all cases, so … that the strong law of large numbers guarantees the convergence. Moreover, the simulation noise is a decreasing function of …

modified version of the stochastic (backward) automatic differentiation.As a test case we consider a hedge simulation requiring …