Monte Carlo Pricing of American Options Using Nonparametric Regression

This paper provides an introduction to Monte Carlo algorithms for pricing American options written on multiple assets, with special emphasis on methods that can be applied in a multi-dimensional setting. Simulated paths can be used to estimate by nonparametric regression the continuation value of the option or the optimal exercise policy and the value functions can then be computed by backward induction. The flexibility of nonparametric regression allows to obtain accurate price estimates with remarkable speed. For illustrative purposes we price one- and two-dimensional American options.