Parallelization and Performance of Portfolio Choice Models
AbstractWe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 114.
Date of creation: 01 Apr 2001
Date of revision:
Contact details of provider:
Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
More information through EDIRC
Parallel Programming; Portfolio Choice;
Find related papers by JEL classification:
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Jurgen A. Doornik & David F. Hendry & Neil Shephard, .
"Computationally-intensive Econometrics using a Distributed Matrix-programming Language,"
2001-W22, Economics Group, Nuffield College, University of Oxford.
- David Hendry & Neil Shephard & Jurgen Doornik, 2001. "Computationally-intensive Econometrics using a Distributed Matrix-programming Language," Economics Series Working Papers 2001-W22, University of Oxford, Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.