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Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation

Author

Listed:
  • Thapar, Rishi
  • Minsky, Bernard
  • Obradovic, M
  • Tang, Qi

Abstract

Portfolio optimisation for a Fund of Hedge Funds (“FoHF”) has to address the asymmetric, non-Gaussian nature of the underlying returns distributions. Furthermore, the objective functions and constraints are not necessarily convex or even smooth. Therefore traditional portfolio optimisation methods such as mean-variance optimisation are not appropriate for such problems and global search optimisation algorithms could serve better to address such problems. Also, in implementing such an approach the goal is to incorporate information as to the future expected outcomes to determine the optimised portfolio rather than optimise a portfolio on historic performance. In this paper, we consider the suitability of global search optimisation algorithms applied to FoHF portfolios, and using one of these algorithms to construct an optimal portfolio of investable hedge fund indices given forecast views of the future and our confidence in such views.

Suggested Citation

  • Thapar, Rishi & Minsky, Bernard & Obradovic, M & Tang, Qi, 2009. "Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation," MPRA Paper 17099, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:17099
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    File URL: https://mpra.ub.uni-muenchen.de/17099/1/MPRA_paper_17099.pdf
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    References listed on IDEAS

    as
    1. Yannick Malevergne & Ali Chabaane & Jean-Paul Laurent & Françoise Turpin, 2006. "Alternative Risk Measures for Alternative Investments," Post-Print hal-02311832, HAL.
    2. Stefano Ciliberti & Imre Kondor & Marc Mezard, 2007. "On the feasibility of portfolio optimization under expected shortfall," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 389-396.
    3. M. Gilli & E. Kellezi & H. Hysi, 2006. "A Data-Driven Optimization Heuristic for Downside Risk Minimization," Computing in Economics and Finance 2006 355, Society for Computational Economics.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    portfolio optimisation; optimization; fund of hedge funds; global search optimisation; direct search; pgsl; hedge fund portfolio;
    All these keywords.

    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
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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