An Implementation of Binomial Method of Option Pricing using Parallel Computing

Abstract

The Binomial method of option pricing is based on iterating over discounted option payoffs in a recursive fashion to calculate the present value of an option. Implementing the Binomial method to exploit the resources of a parallel computing cluster is non-trivial as the method is not easily parallelizable. We propose a procedure to transform the method into an “embarrassingly parallel” problem by mapping Binomial probabilities to Bernoulli paths. We have used the parallel computing capabilities in R with the Rmpi package to implement the methodology on the cluster tara in the UMBC High Performance Computing Facility, which has 82 compute nodes with two quad-core Intel Nehalem processors and 24 GB of memory on a quad-data rate InfiniBand interconnect. With high-performance clusters and multi-core desktops becoming increasingly accessible, we believe that our method will have practical appeal to financial trading firms.