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Robust Mean-Variance Portfolio Selection

Author

Listed:
  • Cédric Perret-Gentil

    (Union Bancaire Privée)

  • Maria-Pia Victoria-Feser

    (HEC,University of Geneva)

Abstract

This paper investigates model risk issues in the context of mean-variance portfolio selection. We analytically and numerically show that, under model misspecification, the use of statistically robust estimates instead of the widely used classical sample mean and covariance is highly beneficial for the stability properties of the mean-variance optimal portfolios. Moreover, we perform simulations leading to the conclusion that, under classical estimation, model risk bias dominates estimation risk bias. Finally, we suggest a diagnostic tool to warn the analyst of the presence of extreme returns that have an abnormally large influence on the optimization results.

Suggested Citation

  • Cédric Perret-Gentil & Maria-Pia Victoria-Feser, 2005. "Robust Mean-Variance Portfolio Selection," FAME Research Paper Series rp140, International Center for Financial Asset Management and Engineering.
    • Handle: RePEc:fam:rpseri:rp140
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    File URL: http://www.swissfinanceinstitute.ch/rp140.pdf
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    References listed on IDEAS

    as
    1. Barry, Christopher B, 1974. "Portfolio Analysis under Uncertain Means, Variances, and Covariances," Journal of Finance, American Finance Association, vol. 29(2), pages 515-522, May.
    2. Alexander, Gordon J & Resnick, Bruce G, 1985. "More on Estimation Risk and Simple Rules for Optimal Portfolio Selection," Journal of Finance, American Finance Association, vol. 40(1), pages 125-133, March.
    3. Victoria-Feser, M.-P., 2000. "Robust Portfolio Selection," Papers 2000.14, Ecole des Hautes Etudes Commerciales, Universite de Geneve-.
    4. 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.
    5. Ter Horst, J.R. & de Roon, F.A. & Werker, B.J.M., 2000. "Incorporating Estimation Risk in Portfolio Choice," Discussion Paper 2000-65, Tilburg University, Center for Economic Research.
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    Citations

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    Cited by:

    1. Hubert, Mia & Dierckx, Goedele & Vanpaemel, Dina, 2013. "Detecting influential data points for the Hill estimator in Pareto-type distributions," Computational Statistics & Data Analysis, Elsevier, vol. 65(C), pages 13-28.
    2. 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.
    3. Giuseppe Pandolfo & Carmela Iorio & Roberta Siciliano & Antonio D’Ambrosio, 2020. "Robust mean-variance portfolio through the weighted $$L^{p}$$ L p depth function," Annals of Operations Research, Springer, vol. 292(1), pages 519-531, September.
    4. Aida Toma & Samuela Leoni-Aubin, 2015. "Robust Portfolio Optimization Using Pseudodistances," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-26, October.
    5. Stanislav Škapa & Tomáš Meluzín & Marek Zinecker, 2013. "A critical evaluation of risk-return characteristics of environmentally focused stock's companies," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 61(2), pages 501-506.

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    More about this item

    Keywords

    Mean-variance e .cient frontier; Outliers; Model risk; Robust es-timation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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