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Parallelization and Performance of Portfolio Choice Models

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  • A. Abdelkhalek, A. Bilas and A. Michaelides

Abstract

We show how applications in computational economics can take advantage of modern parallel architectures to reduce the computation time in a wide array of models that have been, to date, computationally intractable. The specific application comes from solving a portfolio choice model over the lifecycle in the presence of undiversifiable labor income risk, borrowing and short sale constraints. We provide an efficient parallel implementation and introduce a new benchmark for parallel computer architectures from an emerging and important class of applications. We conclude that emerging applications in this area of computational economics exhibit adequate parallelism to achieve, after a number of optimization steps, almost linear speedup for system sizes up to 64 processors on today's hardware shared memory multiprocessors.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 114.

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Date of creation: 01 Apr 2001
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Handle: RePEc:sce:scecf1:114

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Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
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Keywords: Parallel Programming; Portfolio Choice;

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Cited by:
  1. Jurgen A. Doornik & David F. Hendry & Neil Shephard, . "Computationally-intensive Econometrics using a Distributed Matrix-programming Language," Economics Papers 2001-W22, Economics Group, Nuffield College, University of Oxford.

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