Accurate computation of the right tail of the sum of dependent log-normal variates

We study the problem of the Monte Carlo estimation of the right tail of the distribution of the sum of correlated log-normal random variables. While a number of theoretically efficient estimators have been proposed for this setting, using a few numerical examples we illustrate that these published proposals may not always be useful in practical simulations. In other words, we show that the established theoretical efficiency of these estimators does not necessarily convert into Monte Carlo estimators with low variance. As a remedy to this defect, we propose a new estimator for this setting. We demonstrate that, not only is our novel estimator theoretically efficient, but, more importantly, its practical performance is significantly better than that of its competitors.