An efficient GPU-based parallel algorithm for pricing multi-asset American options

Dang, Duy-Minh, Christara, Christina C. and Jackson, Kenneth R. (2012) An efficient GPU-based parallel algorithm for pricing multi-asset American options. Concurrency and Computation: Practice and Experience, 24 8: 849-866. doi:10.1002/cpe.1784

Author Dang, Duy-Minh
Christara, Christina C.
Jackson, Kenneth R.
Title An efficient GPU-based parallel algorithm for pricing multi-asset American options
Journal name Concurrency and Computation: Practice and Experience   Check publisher's open access policy
ISSN 1532-0626
Publication date 2012-06
Year available 2012
Sub-type Article (original research)
DOI 10.1002/cpe.1784
Volume 24
Issue 8
Start page 849
End page 866
Total pages 18
Place of publication Chichester, West Sussex, United Kingdom
Publisher John Wiley and Sons Ltd.
Collection year 2012
Language eng
Formatted abstract
We develop highly efficient parallel PDE-based pricing methods on graphics processing units (GPUs) for multi-asset American options. Our pricing approach is built upon a combination of a discrete penalty approach for the linear complementarity problem arising because of the free boundary and a GPU-based parallel alternating direction implicit approximate factorization technique with finite differences on uniform grids for the solution of the linear algebraic system arising from each penalty iteration. A timestep size selector implemented efficiently on GPUs is used to further increase the efficiency of the methods. We demonstrate the efficiency and accuracy of the parallel numerical methods by pricing American options written on three assets
Keyword Graphics processing units
American option
Multi asset
Parallel computing
Penalty method
Time adaptivity
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Mathematics and Physics
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Citation counts: TR Web of Science Citation Count  Cited 7 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 8 times in Scopus Article | Citations
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Created: Wed, 17 Sep 2014, 16:05:11 EST by Kay Mackie on behalf of School of Mathematics & Physics