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Optimal portfolios using linear programming models


  • Christos Papahristodoulou

    (Mälardalen University, School of Business)

  • Erik Dotzauer

    (Mälardalen University, Department of Mathematics)


The classical Quadratic Programming (QP) formulation of the well-known portfolio selection problem has traditionally been regarded as cumbersome and time consuming. This paper formulates two additional models, (i) maximin, and (ii) minimization of mean absolute deviation. Data from 67 securities over 48 months are used to examine to what extent all three formulations provide similar portfolios. As expected, the maximin formulation yields the highest return and risk, while the QP formulation provides the lowest risk and return, which also creates the efficient frontier. The minimization of mean absolute deviation is close to the QP formulation. When the expected returns are confronted with the true ones at the end of a six months period, the maximin portfolios seem to be the most robust of all.

Suggested Citation

  • Christos Papahristodoulou & Erik Dotzauer, 2005. "Optimal portfolios using linear programming models," Finance 0505006, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpfi:0505006
    Note: Type of Document - pdf. Published in Journal of the Operational research Society (2004) 55, 1169-1177

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    References listed on IDEAS

    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    3. Leon, T. & Liern, V. & Vercher, E., 2002. "Viability of infeasible portfolio selection problems: A fuzzy approach," European Journal of Operational Research, Elsevier, vol. 139(1), pages 178-189, May.
    4. Mansini, Renata & Speranza, Maria Grazia, 1999. "Heuristic algorithms for the portfolio selection problem with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 114(2), pages 219-233, April.
    5. Martin R. Young, 1998. "A Minimax Portfolio Selection Rule with Linear Programming Solution," Management Science, INFORMS, vol. 44(5), pages 673-683, May.
    6. Rudolf, Markus & Wolter, Hans-Jurgen & Zimmermann, Heinz, 1999. "A linear model for tracking error minimization," Journal of Banking & Finance, Elsevier, vol. 23(1), pages 85-103, January.
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    Cited by:

    1. Bartosz Kaszuba, 2012. "Empirical Comparison of Robust Portfolios’ Investment Effects," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(1), pages 047-061, June.
    2. Li, Xiang & Qin, Zhongfeng, 2014. "Interval portfolio selection models within the framework of uncertainty theory," Economic Modelling, Elsevier, vol. 41(C), pages 338-344.
    3. Ghahtarani, Alireza & Najafi, Amir Abbas, 2013. "Robust goal programming for multi-objective portfolio selection problem," Economic Modelling, Elsevier, vol. 33(C), pages 588-592.

    More about this item


    Finance; linear programming; investment analysis; risk analysis;

    JEL classification:

    • G - Financial Economics

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