IDEAS home Printed from
   My bibliography  Save this paper

Parallelization and Performance of Portfolio Choice Models


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


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.

Suggested Citation

  • A. Abdelkhalek, A. Bilas and A. Michaelides, 2001. "Parallelization and Performance of Portfolio Choice Models," Computing in Economics and Finance 2001 114, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:114

    Download full text from publisher

    File URL:
    File Function: main text
    Download Restriction: no

    References listed on IDEAS

    1. Brock, William A & LeBaron, Blake D, 1996. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 94-110, February.
    2. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
    3. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    4. Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
    5. Cheung, Yin-Wong & Friedman, Daniel, 1998. "A comparison of learning and replicator dynamics using experimental data," Journal of Economic Behavior & Organization, Elsevier, vol. 35(3), pages 263-280, April.
    6. Ed Hopkins, 2002. "Two Competing Models of How People Learn in Games," Econometrica, Econometric Society, vol. 70(6), pages 2141-2166, November.
    7. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    8. Allan Timmermann, 1996. "Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning," Review of Economic Studies, Oxford University Press, vol. 63(4), pages 523-557.
    9. de Fontnouvelle, Patrick, 2000. "Information Dynamics In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(02), pages 139-169, June.
    10. Marcet, Albert & Sargent, Thomas J, 1989. "Convergence of Least-Squares Learning in Environments with Hidden State Variables and Private Information," Journal of Political Economy, University of Chicago Press, vol. 97(6), pages 1306-1322, December.
    11. Droste, Edward & Hommes, Cars & Tuinstra, Jan, 2002. "Endogenous fluctuations under evolutionary pressure in Cournot competition," Games and Economic Behavior, Elsevier, vol. 40(2), pages 232-269, August.
    12. Bray, Margaret, 1982. "Learning, estimation, and the stability of rational expectations," Journal of Economic Theory, Elsevier, vol. 26(2), pages 318-339, April.
    13. Hellwig, Martin F., 1980. "On the aggregation of information in competitive markets," Journal of Economic Theory, Elsevier, vol. 22(3), pages 477-498, June.
    14. Sethi, Rajiv & Franke, Reiner, 1995. "Behavioural Heterogeneity under Evolutionary Pressure: Macroeconomic Implications of Costly Optimisation," Economic Journal, Royal Economic Society, vol. 105(430), pages 583-600, May.
    15. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    16. Barberis, Nicholas & Shleifer, Andrei, 2003. "Style investing," Journal of Financial Economics, Elsevier, vol. 68(2), pages 161-199, May.
    17. Routledge, Bryan R, 1999. "Adaptive Learning in Financial Markets," Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 1165-1202.
    18. Branch, William A. & McGough, Bruce, 2008. "Replicator dynamics in a Cobweb model with rationally heterogeneous expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 65(2), pages 224-244, February.
    19. repec:hrv:faseco:30747193 is not listed on IDEAS
    20. Hussman, John P., 1992. "Market efficiency and inefficiency in rational expectations equilibria : Dynamic effects of heterogeneous information and noise," Journal of Economic Dynamics and Control, Elsevier, vol. 16(3-4), pages 655-680.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    More about this item


    Parallel Programming; Portfolio Choice;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sce:scecf1:114. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.