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Portfolio Optimization with Combinatorial and Downside Return Constraints

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Modeling and Optimization: Theory and Applications

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 62))

Abstract

We study a probabilistic portfolio optimization model in which trading restrictions modeled with combinatorial constraints are accounted for. We provide several deterministic reformulations equivalent to this stochastic programming problem and discuss their computational efficiency. The reformulated problem takes the form of a mixed-integer nonlinear problem and is solved with an exact outer approximation algorithm. This latter is based on the early recognition of the problem structure and permits a hierarchical organization of the computations. Computational tests show the contribution of the proposed algorithm that outperforms the Cplex 12.4 solver in terms of computational time and quality of the obtained solutions.

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Author information

Authors and Affiliations

  1. Department of Decision Sciences, George Washington University, 2201 G Street, Suite 415, NW Washington, DC, USA

    Miguel A. Lejeune

Authors
  1. Miguel A. Lejeune
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Corresponding author

Correspondence to Miguel A. Lejeune .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania, USA

    Luis F. Zuluaga

  2. Dept. Industrial & Systems Engineering, Lehigh University, Bethlehem, Pennsylvania, USA

    Tamás Terlaky

Appendix

Appendix

Table 2 Computational results for thirty-two problem instances
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Lejeune, M.A. (2013). Portfolio Optimization with Combinatorial and Downside Return Constraints. In: Zuluaga, L., Terlaky, T. (eds) Modeling and Optimization: Theory and Applications. Springer Proceedings in Mathematics & Statistics, vol 62. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8987-0_2

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