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Pricing derivatives on graphics processing units using Monte Carlo simulation

Authors :
Patrick Mercier
Lokman A. Abbas-Turki
Stéphane Vialle
Bernard Lapeyre
Source :
Concurrency and Computation: Practice and Experience. 26:1679-1697
Publication Year :
2012
Publisher :
Wiley, 2012.

Abstract

This paper is about using the existing Monte Carlo approach for pricing European and American contracts on a state-of-the-art graphics processing unit GPU architecture. First, we adapt on a cluster of GPUs two different suitable paradigms of parallelizing random number generators, which were developed for CPU clusters. Because in financial applications, we request results within seconds of simulation, the sufficiently large computations should be implemented on a cluster of machines. Thus, we make the European contract comparison between CPUs and GPUs using from one up to 16 nodes of a CPU/GPU cluster. We show that using GPUs for European contracts reduces the execution time by~40 and diminishes the energy consumed by~50 during the simulation. In the second set of experiments, we investigate the benefits of using GPUs' parallelization for pricing American options that require solving an optimal stopping problem and which we implement using the Longstaff and Schwartz regression method. The speedup result obtained for American options varies between two and 10 according to the number of generated paths, the dimensions, and the time discretization. Copyright © 2012 John Wiley & Sons, Ltd.

Details

ISSN :
15320626
Volume :
26
Database :
OpenAIRE
Journal :
Concurrency and Computation: Practice and Experience
Accession number :
edsair.doi...........bd7fdbb18601899287e0a8afcec708b2
Full Text :
https://doi.org/10.1002/cpe.2862