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Robust portfolio allocation under discrete asset choice constraints

Author

Listed:
  • Nalan Gülpınar

    (Warwick Business School, The University of Warwick)

  • Kabir Katata
  • Dessislava A Pachamanova
Abstract
The mean-variance portfolio allocation model is very sensitive to estimation errors in the model parameters. Robust optimization is a technique used to incorporate the uncertainty introduced by estimation errors directly into portfolio allocation. Practitioners are often faced with complex constraints on the portfolio structure such as limits on the number of securities in the portfolio, which are modelled with discrete variables, and introduce discontinuities in the efficient frontier. This article investigates the size of discontinuities in the efficient frontiers obtained by the classical and robust mean-variance models under such discrete asset choice constraints, as well as the impact of portfolio size on the discontinuity being considered. In addition, we analyse the effects of applying discrete asset choice restrictions to the portfolio selection problem, as well as using estimated and true parameters in the computation of the classical and robust mean-variance investment strategies under discrete asset choice constraints. Computational experiments reveal reduction of the size of discontinuity when using robust optimization mean-variance models.

Suggested Citation

  • Nalan Gülpınar & Kabir Katata & Dessislava A Pachamanova, 2011. "Robust portfolio allocation under discrete asset choice constraints," Journal of Asset Management, Palgrave Macmillan, vol. 12(1), pages 67-83, April.
    • Handle: RePEc:pal:assmgt:v:12:y:2011:i:1:d:10.1057_jam.2010.15
    DOI: 10.1057/jam.2010.15
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    References listed on IDEAS

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    1. Jorion, Philippe, 1985. "International Portfolio Diversification with Estimation Risk," The Journal of Business, University of Chicago Press, vol. 58(3), pages 259-278, July.
    2. Sebastián Ceria & Robert A Stubbs, 2006. "Incorporating estimation errors into portfolio selection: Robust portfolio construction," Journal of Asset Management, Palgrave Macmillan, vol. 7(2), pages 109-127, July.
    3. Nalan Gülpinar & Berç Rustem & Stanislav Žaković, 2007. "Stochastic Optimization and Worst-case Decisions," Lecture Notes in Economics and Mathematical Systems, in: Don Grundel & Robert Murphey & Panos Pardalos & Oleg Prokopyev (ed.), Cooperative Systems, pages 317-338, Springer.
    4. N. J. Jobst & M. D. Horniman & C. A. Lucas & G. Mitra, 2001. "Computational aspects of alternative portfolio selection models in the presence of discrete asset choice constraints," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 489-501.
    5. D. Goldfarb & G. Iyengar, 2003. "Robust Portfolio Selection Problems," Mathematics of Operations Research, INFORMS, vol. 28(1), pages 1-38, February.
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    Cited by:

    1. Gülpınar, Nalân & Çanakoḡlu, Ethem, 2017. "Robust portfolio selection problem under temperature uncertainty," European Journal of Operational Research, Elsevier, vol. 256(2), pages 500-523.
    2. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.
    3. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
    4. Panos Xidonas & Ralph Steuer & Christis Hassapis, 2020. "Robust portfolio optimization: a categorized bibliographic review," Annals of Operations Research, Springer, vol. 292(1), pages 533-552, September.
    5. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2018. "Recent advancements in robust optimization for investment management," Annals of Operations Research, Springer, vol. 266(1), pages 183-198, July.
    6. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.

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