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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. 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.
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    4. 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.
    5. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    6. Mark Britten‐Jones, 1999. "The Sampling Error in Estimates of Mean‐Variance Efficient Portfolio Weights," Journal of Finance, American Finance Association, vol. 54(2), pages 655-671, April.
    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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