Monte Carlo Valuation of American Options through Computation of the Optimal Exercise Frontier
提出一种基于最优行权边界计算的蒙特卡洛方法，用于定价多维美式期权，通过递归计算百慕大期权的行权边界，并利用普通蒙特卡洛模拟得到低偏估计量。
Abstract This paper introduces a Monte Carlo simulation method for pricing multidimensional American options based on the computation of the optimal exercise frontier. We consider Bermudan options that can be exercised at a finite number of times and compute the optimal exercise frontier recursively. We show that for every date of possible exercise, any single point of the optimal exercise frontier is a fixed point of a simple algorithm. Once the frontier is computed, we use plain vanilla Monte Carlo simulation to price the option and obtain a low-biased estimator. We illustrate the method with applications to several types of options.