UMBC Center for Interdisciplinary Research and Consulting (CIRC)
http://hdl.handle.net/11603/11404
Mon, 24 Jun 2019 18:27:37 GMT2019-06-24T18:27:37ZUMBC Center for Interdisciplinary Research and Consulting (CIRC)http://mdsoar.org:80/bitstream/id/8e17a9a3-7d6e-4a74-8777-c6c0f8ab86a6/
http://hdl.handle.net/11603/11404
Introduction to Distributed Computing with pbdR at the UMBC High Performance Computing Facility
http://hdl.handle.net/11603/11562
Introduction to Distributed Computing with pbdR at the UMBC High Performance Computing Facility
Raim, Andrew M.
Wed, 26 Jun 2013 00:00:00 GMThttp://hdl.handle.net/11603/115622013-06-26T00:00:00ZAn Implementation of Binomial Method of Option Pricing using Parallel Computing
http://hdl.handle.net/11603/11536
An Implementation of Binomial Method of Option Pricing using Parallel Computing
Popuri, Sai K.; Raim, Andrew M.; Neerchal, Nagaraj K.; Gobbert, Matthias K.
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.
http://hdl.handle.net/11603/11536