This paper considers the problem of pricing options with early-exercise features whose pay-off depends on several sources of uncertainty. We propose a stochastic grid method for estimating the optimal exercise policy and using this policy to obtain a low-biased estimator for high-dimensional...

In this work, we propose a one time-step Monte Carlo method for the SABR model. We base our approach on an accurate approximation of the cumulative distribution function of the integrated variance (conditional on the SABR volatility process), using Fourier techniques and a copula. Resulting is a...

This paper describes a practical simulation-based algorithm, which we call the <I>Stochastic Grid Bundling Method </I> (SGBM) for pricing multi-dimensional Bermudan (i.e. discretely exercisable) options. The method generates a direct estimator of the option price, an optimal early-exercise policy as...</i>