  We introduce a stacking version of the Monte Carlo algorithm in the context
of option pricing. Introduced recently for aeronautic computations, this simple
technique, in the spirit of current machine learning ideas, learns control
variates by approximating Monte Carlo draws with some specified function. We
describe the method from first principles and suggest appropriate fits, and
show its efficiency to evaluate European and Asian Call options in constant and
stochastic volatility models.
