IDEAS home Printed from https://ideas.repec.org/p/chf/rpseri/rp0817.html
   My bibliography  Save this paper

Distributed Optimisation of a Portfolio's Omega

Author

Listed:
  • Manfred Gilli

    (Department of Econometrics, University of Geneva and Swiss Finance Institute)

  • Enrico Schumann

    (Department of Econometrics, University of Geneva)

Abstract

We investigate portfolio selection with alternative objective functions in a distributed computing environment. In particular, we optimise a portfolio's 'Omega' which is the ratio of two partial moments of the returns distributions. Since finding optimal portfolios under such performance measures and realistic constraints leads to non-convex problems, we suggest to solve the problem with a heuristic method called Threshold Accepting (TA). TA is a very flexible technique as it requires no simplifications of the problem and allows for a straightforward implementation of all kinds of constraints. Applying this algorithm to actual data, we find that TA is well-adapted to optimisation problems of this type. Furthermore, we show that the computations can easily be distributed which leads to considerable speedups.

Suggested Citation

  • Manfred Gilli & Enrico Schumann, 2008. "Distributed Optimisation of a Portfolio's Omega," Swiss Finance Institute Research Paper Series 08-17, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp0817
    as

    Download full text from publisher

    File URL: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1156355
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Caporin, Massimiliano & Costola, Michele & Jannin, Gregory & Maillet, Bertrand, 2018. "“On the (Ab)use of Omega?”," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 11-33.
    2. Manfred Gilli & Enrico Schumann, 2012. "Heuristic optimisation in financial modelling," Annals of Operations Research, Springer, vol. 193(1), pages 129-158, March.
    3. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    4. Zhu, Min, 2013. "Return distribution predictability and its implications for portfolio selection," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 209-223.
    5. Abdallah Ben Saida & Jean-luc Prigent, 2018. "On the robustness of portfolio allocation under copula misspecification," Annals of Operations Research, Springer, vol. 262(2), pages 631-652, March.
    6. Guastaroba, G. & Mansini, R. & Ogryczak, W. & Speranza, M.G., 2016. "Linear programming models based on Omega ratio for the Enhanced Index Tracking Problem," European Journal of Operational Research, Elsevier, vol. 251(3), pages 938-956.

    More about this item

    Keywords

    Optimization heuristics; Threshold Accepting; Portfolio Optimization; Distributed Computing;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:chf:rpseri:rp0817. 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: Ridima Mittal (email available below). General contact details of provider: https://edirc.repec.org/data/fameech.html .

    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.