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Robust covariance estimators for mean-variance portfolio optimization with transaction lots

Author

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  • Rosadi, Dedi
  • Setiawan, Ezra Putranda
  • Templ, Matthias
  • Filzmoser, Peter

Abstract

This study presents an improvement to the mean-variance portfolio optimization model, by considering both the integer transaction lots and a robust estimator of the covariance matrices. Four robust estimators were tested, namely the Minimum Covariance Determinant, the S, the MM, and the Orthogonalized Gnanadesikan–Kettenring estimator. These integer optimization problems were solved using genetic algorithms. We introduce the lot turnover measure, a modified portfolio turnover, and the Robust Sharpe Ratio as the measure of portfolio performance. Based on the simulation studies and the empirical results, this study shows that the robust estimators outperform the classical MLE when data contain outliers and when the lots have moderate sizes, e.g. 500 shares or less per lot.

Suggested Citation

  • Rosadi, Dedi & Setiawan, Ezra Putranda & Templ, Matthias & Filzmoser, Peter, 2020. "Robust covariance estimators for mean-variance portfolio optimization with transaction lots," Operations Research Perspectives, Elsevier, vol. 7(C).
    • Handle: RePEc:eee:oprepe:v:7:y:2020:i:c:s2214716020300440
    DOI: 10.1016/j.orp.2020.100154
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    References listed on IDEAS

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    1. Lin, Chang-Chun & Liu, Yi-Ting, 2008. "Genetic algorithms for portfolio selection problems with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 185(1), pages 393-404, February.
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    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. Victor DeMiguel & Francisco J. Nogales, 2009. "Portfolio Selection with Robust Estimation," Operations Research, INFORMS, vol. 57(3), pages 560-577, June.
    6. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    7. D. Goldfarb & G. Iyengar, 2003. "Robust Portfolio Selection Problems," Mathematics of Operations Research, INFORMS, vol. 28(1), pages 1-38, February.
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    Cited by:

    1. Fassino, Claudia & Torrente, Maria-Laura & Uberti, Pierpaolo, 2022. "A singular value decomposition based approach to handle ill-conditioning in optimization problems with applications to portfolio theory," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).

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