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Markowitz versus Michaud: Portfolio optimization strategies reconsidered

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  • Becker, Franziska
  • Gürtler, Marc
  • Hibbeln, Martin

Abstract

Several attempts have been made to reduce the impact of estimation errors on the optimal portfolio composition. On the one hand, improved estimators of the necessary moments have been developed and on the other hand, heuristic methods have been generated to enhance the portfolio performance, for instance the resampled efficiency of Michaud (1998). We compare the out-ofsample performance of traditional Mean-Variance optimization by Markowitz (1952) with Michaud's resampled efficiency in a comprehensive simulation study for a large number of relevant estimators appearing in the literature. In this context we consider different estimation periods as well as unconstrained and constrained portfolio optimization problems. The main finding of our simu-lation study concerning the optimization approach is that Markowitz outperforms Michaud on average. Furthermore, the estimation strategy of Frost/Savarino (1988) proves to work excellent in all analyzed situations.

Suggested Citation

  • Becker, Franziska & Gürtler, Marc & Hibbeln, Martin, 2009. "Markowitz versus Michaud: Portfolio optimization strategies reconsidered," Working Papers IF30V3, Technische Universität Braunschweig, Institute of Finance.
    • Handle: RePEc:zbw:tbsifw:if30v3
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    References listed on IDEAS

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    1. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    2. Vijay K. Chopra & Chris R. Hensel & Andrew L. Turner, 1993. "Massaging Mean-Variance Inputs: Returns from Alternative Global Investment Strategies in the 1980s," Management Science, INFORMS, vol. 39(7), pages 845-855, July.
    3. Bernd Scherer, 2006. "A note on the out-of-sample performance of resampled efficiency," Journal of Asset Management, Palgrave Macmillan, vol. 7(3), pages 170-178, September.
    4. Frost, Peter A. & Savarino, James E., 1986. "An Empirical Bayes Approach to Efficient Portfolio Selection," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(3), pages 293-305, September.
    5. Ledoit, Olivier & Wolf, Michael, 2003. "Improved estimation of the covariance matrix of stock returns with an application to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 603-621, December.
    6. Yusif Simaan, 1997. "Estimation Risk in Portfolio Selection: The Mean Variance Model Versus the Mean Absolute Deviation Model," Management Science, INFORMS, vol. 43(10), pages 1437-1446, October.
    7. Lorenzo Garlappi & Raman Uppal & Tan Wang, 2007. "Portfolio Selection with Parameter and Model Uncertainty: A Multi-Prior Approach," Review of Financial Studies, Society for Financial Studies, vol. 20(1), pages 41-81, January.
    8. Andrew L. Turner & Chris R. Hensel, 1993. "Were the Returns from Stocks and Bonds of Different Countries Really Different in the 1980s?," Management Science, INFORMS, vol. 39(7), pages 835-844, July.
    9. Jorion, Philippe, 1985. "International Portfolio Diversification with Estimation Risk," The Journal of Business, University of Chicago Press, vol. 58(3), pages 259-278, July.
    10. Michael J. Best & Robert R. Grauer, 1991. "Sensitivity Analysis for Mean-Variance Portfolio Problems," Management Science, INFORMS, vol. 37(8), pages 980-989, August.
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    More about this item

    Keywords

    portfolio selection; estimators of moments; simulation study; mean-variance optimization; resampled efficiency;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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