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Quadratic programming for portfolio planning: Insights into algorithmic and computational issues

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  • Gautam Mitra

    (CARISMA — The Centre for the Analysis of Risk and Optimisation Modelling Applications, Brunel University)

  • Frank Ellison
  • Alan Scowcroft

Abstract

Convex quadratic programming (QP) as applied to portfolio planning is established and well understood. In this paper, presented in two parts, we highlight the importance of choosing an algorithm that processes a family of problems efficiently. In Part I in particular we describe an adaptation of the simplex method for QP. The method takes advantage of the sparse features of simplex and the use of the duality property makes it ideally suited for processing the discrete optimisation models. Part II (to be published in issue 8/4) of the paper considers a family of discrete QP formulations of the portfolio problem, which captures threshold constraints and cardinality restrictions. We describe the adaptation of a novel method ‘branch, fix and relax’ to process this class of models efficiently. Theory and computational results are presented.

Suggested Citation

  • Gautam Mitra & Frank Ellison & Alan Scowcroft, 2007. "Quadratic programming for portfolio planning: Insights into algorithmic and computational issues," Journal of Asset Management, Palgrave Macmillan, vol. 8(3), pages 200-214, September.
    • Handle: RePEc:pal:assmgt:v:8:y:2007:i:3:d:10.1057_palgrave.jam.2250075
    DOI: 10.1057/palgrave.jam.2250075
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    References listed on IDEAS

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    Cited by:

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    2. P. Bonami & M. A. Lejeune, 2009. "An Exact Solution Approach for Portfolio Optimization Problems Under Stochastic and Integer Constraints," Operations Research, INFORMS, vol. 57(3), pages 650-670, June.
    3. Panos Xidonas & Christis Hassapis & George Mavrotas & Christos Staikouras & Constantin Zopounidis, 2018. "Multiobjective portfolio optimization: bridging mathematical theory with asset management practice," Annals of Operations Research, Springer, vol. 267(1), pages 585-606, August.
    4. Xiaojin Zheng & Xiaoling Sun & Duan Li, 2014. "Improving the Performance of MIQP Solvers for Quadratic Programs with Cardinality and Minimum Threshold Constraints: A Semidefinite Program Approach," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 690-703, November.

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