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On the application of an Augmented Lagrangian algorithm to some portfolio problems

Author

Listed:
  • E. G. Birgin

    (University of São Paulo)

  • J. M. Martínez

    (State University of Campinas)

Abstract

Algencan is a freely available piece of software that aims to solve smooth large-scale constrained optimization problems. When applied to specific problems, obtaining a good performance in terms of efficacy and efficiency may depend on careful choices of options and parameters. In the present paper, the application of Algencan to four portfolio optimization problems is discussed and numerical results are presented and evaluated.

Suggested Citation

  • E. G. Birgin & J. M. Martínez, 2016. "On the application of an Augmented Lagrangian algorithm to some portfolio problems," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(1), pages 79-92, February.
    • Handle: RePEc:spr:eurjco:v:4:y:2016:i:1:d:10.1007_s13675-015-0052-9
    DOI: 10.1007/s13675-015-0052-9
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    References listed on IDEAS

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    1. Churlzu Lim & Hanif Sherali & Stan Uryasev, 2010. "Portfolio optimization by minimizing conditional value-at-risk via nondifferentiable optimization," Computational Optimization and Applications, Springer, vol. 46(3), pages 391-415, July.
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    3. Alexander, S. & Coleman, T.F. & Li, Y., 2006. "Minimizing CVaR and VaR for a portfolio of derivatives," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 583-605, February.
    4. E. Birgin & L. Bueno & N. Krejić & J. Martínez, 2011. "Low order-value approach for solving VaR-constrained optimization problems," Journal of Global Optimization, Springer, vol. 51(4), pages 715-742, December.
    5. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    6. E. Birgin & J. Martínez & L. Prudente, 2014. "Augmented Lagrangians with possible infeasibility and finite termination for global nonlinear programming," Journal of Global Optimization, Springer, vol. 58(2), pages 207-242, February.
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