This note presents a simple, robust and computationally efficient way to calculate expectations of arbitrary future payoffs within the context of a Monte Carlo forward-induction methodology. The technique complements existing approximation techniques: while virtually all existing approximation...

The point estimator used in naive Monte Carlo sampling weights all the computed function evaluations equally, and it does not take into account the precise locations at which the function evaluations are made. In this note, we consider one-dimensional integration problems in which the integrand...