IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v20y2002i3p177-90.html
   My bibliography  Save this article

Local Search Techniques for Constrained Portfolio Selection Problems

Author

Listed:
  • Schaerf, Andrea

Abstract

We consider the problem of selecting a portfolio of assets that provides the investor a suitable balance of expected return and risk. With respect to the seminal mean-variance model of Markowitz, we consider additional constraints on the cardinality of the portfolio and on the quantity of individual shares. Such constraints better capture the real-world trading system, but make the problem more difficult to be solved with exact methods. We explore the use of local search techniques, mainly tabu search, for the portfolio selection problem. We compare the combine previous work on portfolio selection that makes use of the local search approach and we propose new algorithms that combined different neighborhood relations. In addition, we show how the use of randomization and of a simple form of adaptiveness simplifies the setting of a large number of critical parameters. Finally, we show how our techniques perform on public benchmarks. Copyright 2002 by Kluwer Academic Publishers

Suggested Citation

  • Schaerf, Andrea, 2002. "Local Search Techniques for Constrained Portfolio Selection Problems," Computational Economics, Springer;Society for Computational Economics, vol. 20(3), pages 177-190, December.
    • Handle: RePEc:kap:compec:v:20:y:2002:i:3:p:177-90
    as

    Download full text from publisher

    File URL: http://journals.kluweronline.com/issn/0927-7099/contents
    Download Restriction: Access to the full text of the articles in this series is restricted.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Konstantinos Anagnostopoulos & Georgios Mamanis, 2011. "Multiobjective evolutionary algorithms for complex portfolio optimization problems," Computational Management Science, Springer, vol. 8(3), pages 259-279, August.
    2. Xi-li Zhang & Wei-Guo Zhang & Wei-jun Xu & Wei-Lin Xiao, 2010. "Possibilistic Approaches to Portfolio Selection Problem with General Transaction Costs and a CLPSO Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 36(3), pages 191-200, October.
    3. Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2015. "Linear vs. quadratic portfolio selection models with hard real-world constraints," Computational Management Science, Springer, vol. 12(3), pages 345-370, July.
    4. Marco Corazza & Giacomo Di Tollo & Giovanni Fasano & Raffaele Pesenti, 2015. "A novel initialization of PSO for costly portfolio selection problems," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
    5. Branke, J. & Scheckenbach, B. & Stein, M. & Deb, K. & Schmeck, H., 2009. "Portfolio optimization with an envelope-based multi-objective evolutionary algorithm," European Journal of Operational Research, Elsevier, vol. 199(3), pages 684-693, December.
    6. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2011. "Heuristic algorithms for the cardinality constrained efficient frontier," European Journal of Operational Research, Elsevier, vol. 213(3), pages 538-550, September.
    7. Yucheng Kao & Hsiu-Tzu Cheng, 2013. "Bacterial Foraging Optimization Approach to Portfolio Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 453-470, December.
    8. Xiaolou Yang, 2006. "Improving Portfolio Efficiency: A Genetic Algorithm Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 1-14, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    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:kap:compec:v:20:y:2002:i:3:p:177-90. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.