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Proceedings Paper

Portable parallel portfolio optimization in the Aurora Financial Management System
Author(s): Erwin Laure; Hans Moritsch
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Paper Abstract

Financial planning problems are formulated as large scale, stochastic, multiperiod, tree structured optimization problems. An efficient technique for solving this kind of problems is the nested Benders decomposition method. In this paper we present a parallel, portable, asynchronous implementation of this technique. To achieve our portability goals we elected the programming language Java for our implementation and used a high level Java based framework, called OpusJava, for expressing the parallelism potential as well as synchronization constraints. Our implementation is embedded within a modular decision support tool for portfolio and asset liability management, the Aurora Financial Management System.

Paper Details

Date Published: 27 July 2001
PDF: 12 pages
Proc. SPIE 4528, Commercial Applications for High-Performance Computing, (27 July 2001); doi: 10.1117/12.434871
Show Author Affiliations
Erwin Laure, Univ. of Vienna (Austria)
Hans Moritsch, Univ. of Vienna (Austria)

Published in SPIE Proceedings Vol. 4528:
Commercial Applications for High-Performance Computing
Howard Jay Siegel, Editor(s)

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