  We investigate the use of Antithetic Variables, Control Variates and
Importance Sampling to reduce the statistical errors of option sensitivities
calculated with the Likelihood Ratio Method in Monte Carlo. We show how
Antithetic Variables solve the well-known problem of the divergence of the
variance of Delta for short maturities and small volatilities. With numerical
examples within a Gaussian Copula framework, we show how simple Control
Variates and Importance Sampling strategies provide computational savings up to
several orders of magnitude.
