Parallel American Monte Carlo

A Parallel Quasi-Monte Carlo Approach to Pricing American Options

Parallel Monte Carlo Methods

This paper is the key paper in my Survey-based term project. The author argues that Monte Carlo algorithms are ideally suited to parallel computing, and that “parallel Monte Carlo” should be more widely used. Therefore I consider many of issues can be raised by use Parallel Monte Carlo method. And from this paper I also can discuss the possibilities of parallel Markov chain Monte Carlo which is...

Parallel Monte-Carlo Tree Search

Monte-Carlo Tree Search (MCTS) is a new best-first search method that started a revolution in the field of Computer Go. Parallelizing MCTS is an important way to increase the strength of any Go program. In this article, we discuss three parallelization methods for MCTS: leaf parallelization, root parallelization, and tree parallelization. To be effective tree parallelization requires two techni...

Monte Carlo Valuation of American Options

This paper introduces a dual way to price American options, based on simulating the paths of the option payoff, and of a judiciously chosen Lagrangian martingale. Taking the pathwise maximum of the payoff less the martingale provides an upper bound for the price of the option, and this bound is sharp for the optimal choice of Lagrangian martingale. As a first exploration of this method, four ex...

Monte Carlo Simulation for American Options

This paper reviews the basic properties of American options and the difficulties of applying Monte Carlo valuation to American options. Asymptotic results by Keller and co-workers are described for the singularity in the early exercise boundary for time t near the final time T . Recent progress on application of Monte Carlo to American options is described including the following: Branching pro...