Popuri, Sai K.Raim, Andrew M.Neerchal, Nagaraj K.Gobbert, Matthias K.2018-10-152018-10-15http://hdl.handle.net/11603/11536The 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.11 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.OptionCallPutBinomial ModelBernoulli PathParallel ComputingUMBC High Performance Computing Facility (HPCF)An Implementation of Binomial Method of Option Pricing using Parallel ComputingText