An Efficient GPU-Based Parallel Algorithm for Pricing Multi-Asset American Options

15 Pages Posted: 8 Sep 2010 Last revised: 2 Apr 2011

See all articles by Duy-Minh Dang

Duy-Minh Dang

University of Queensland - School of Mathematics and Physics

Christina Christara

University of Toronto - Department of Computer Science

Kenneth R. Jackson

University of Toronto - Department of Computer Science

Date Written: January 17, 2011

Abstract

We develop highly-efficient parallel Partial Differential Equation (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 due to 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.

Keywords: American Option, Multi-Asset, Penalty Method, Alternating Direction Implicit Approximate Factorization (ADI-AF), time adaptivity, Graphics Processing Units, GPUs, Parallel Computing, Finite Difference

JEL Classification: E40, E43, G12, G13, C61, C63

Suggested Citation

Dang, Duy-Minh and Christara, Christina and Jackson, Kenneth R., An Efficient GPU-Based Parallel Algorithm for Pricing Multi-Asset American Options (January 17, 2011). Available at SSRN: https://ssrn.com/abstract=1673626 or http://dx.doi.org/10.2139/ssrn.1673626

Duy-Minh Dang (Contact Author)

University of Queensland - School of Mathematics and Physics ( email )

Priestly Building
St Lucia
Brisbane, Queesland 4067
Australia

HOME PAGE: http://people.smp.uq.edu.au/Duy-MinhDang/

Christina Christara

University of Toronto - Department of Computer Science ( email )

Department of Computer Science
University of Toronto
Toronto, Ontario M5S 3G4
Canada

Kenneth R. Jackson

University of Toronto - Department of Computer Science ( email )

Sandford Fleming Building
10 King's College Road, Room 3302
Toronto, Ontario M5S 3G4
Canada

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