Pricing Higher-Dimensional American Options Using The Stochastic Grid Method

This paper considers the problem of pricing options with early-exercise features whose payo depends on several sources of uncertainty. We propose a stochastic grid method for estimating the upper and lower bound values of high-dimensional American options. The method is a hybrid of the least squares method of Longsta and Schwartz (2001) [22], the stochastic mesh method of Broadie and Glasserman (2004) [11], and stratified state aggregation along the pay-off method of Barraquand and Martineau (1995) [3]. Numerical results are given for single asset Bermudan options, Bermudan max options, Bermudan options on the arithmetic mean of a collection of stocks.