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An Integer Programming Algorithm for Portfolio Selection

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  • Bruce Faaland

    (University of Washington)

Abstract

A mean-variance portfolio selection model suitable for the small investor is formulated as a sequence of quadratic integer programming problems. The special structure of these quadratic problems is exploited in a partial enumeration algorithm which uses cutting planes to accelerate convergence. Computational experience is reported on problems ranging in size from fifteen to fifty variables.

Suggested Citation

  • Bruce Faaland, 1974. "An Integer Programming Algorithm for Portfolio Selection," Management Science, INFORMS, vol. 20(10), pages 1376-1384, June.
    • Handle: RePEc:inm:ormnsc:v:20:y:1974:i:10:p:1376-1384
    DOI: 10.1287/mnsc.20.10.1376
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    Cited by:

    1. Sankaran, Jayaram K. & Patil, Ajay A., 1999. "On the optimal selection of portfolios under limited diversification," Journal of Banking & Finance, Elsevier, vol. 23(11), pages 1655-1666, November.
    2. D. Quadri & E. Soutif & P. Tolla, 2009. "Exact solution method to solve large scale integer quadratic multidimensional knapsack problems," Journal of Combinatorial Optimization, Springer, vol. 17(2), pages 157-167, February.
    3. White, D.J., 1998. "Epsilon-dominating solutions in mean-variance portfolio analysis," European Journal of Operational Research, Elsevier, vol. 105(3), pages 457-466, March.
    4. Federico Della Croce & Dominique Quadri, 2012. "Improving an exact approach for solving separable integer quadratic knapsack problems," Journal of Combinatorial Optimization, Springer, vol. 23(1), pages 21-28, January.

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