Control Variates

Abstract Monte Carlo simulation methods are widely used in several scientific disciplines. They are flexible and easy to apply, but their corresponding error is sometimes deemed too large. This error can be reduced by increasing the sample size, but a more effective approach is to apply cleverly designedvariance reduction techniques. Control variates is an example of such a technique. It aims at reducing the Monte Carlo estimator's variance using a correcting factor that depends on the distance between a control variate and its expectation. This article explains how to use this technique and why it works.