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Massaging Mean-Variance Inputs: Returns from Alternative Global Investment Strategies in the 1980s

Author

Listed:
  • Vijay K. Chopra

    (Frank Russell Company, 909 "A" Street, Tacoma, Washington 98402)

  • Chris R. Hensel

    (Frank Russell Company, 909 "A" Street, Tacoma, Washington 98402)

  • Andrew L. Turner

    (Frank Russell Company, 909 "A" Street, Tacoma, Washington 98402)

Abstract

This paper explores the impact of adjustments to the inputs on total returns, terminal wealth, and portfolio turnover in an unconstrained monthly mean-variance (MV) asset allocation over time. It is well known that MV allocations are very sensitive to small forecast errors in the means and covariances. This sensitivity is especially pronounced for errors in means. One way to control this sensitivity to forecast errors is to use Stein estimation. We examined three naive applications of Stein estimation for six individual country stock indexes, five country bond indexes and five cash indexes. This study has two major conclusions. First, any of the suggested adjustments to inputs dominate the results of an unadjusted-input MV optimization. Adjusted-input portfolios have higher mean return, less variance and greater terminal wealth than unadjusted-input portfolios. Second, these improvements become even greater with transaction costs.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:ormnsc:v:39:y:1993:i:7:p:845-855
    DOI: 10.1287/mnsc.39.7.845
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    Citations

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    Cited by:

    1. Becker, Franziska & Gürtler, Marc & Hibbeln, Martin, 2009. "Markowitz versus Michaud: Portfolio optimization strategies reconsidered," Working Papers IF30V3, Technische Universität Braunschweig, Institute of Finance.
    2. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Working Papers 202111, Geary Institute, University College Dublin.
    3. Yuntaek Pae & Navid Sabbaghi, 2019. "Strategies for choosing an uncertainty budget in log-robust portfolio management," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 1-24, June.
    4. Jacobs, Heiko & Müller, Sebastian & Weber, Martin, 2014. "How should individual investors diversify? An empirical evaluation of alternative asset allocation policies," Journal of Financial Markets, Elsevier, vol. 19(C), pages 62-85.
    5. Stevenson, Simon, 2001. "Emerging markets, downside risk and the asset allocation decision," Emerging Markets Review, Elsevier, vol. 2(1), pages 50-66, March.
    6. Bai, Zhidong & Li, Hua & Wong, Wing-Keung, 2013. "The best estimation for high-dimensional Markowitz mean-variance optimization," MPRA Paper 43862, University Library of Munich, Germany.
    7. D. Goldfarb & G. Iyengar, 2003. "Robust Portfolio Selection Problems," Mathematics of Operations Research, INFORMS, vol. 28(1), pages 1-38, February.
    8. Gilmore, Claire G. & McManus, Ginette M. & Tezel, Ahmet, 2005. "Portfolio allocations and the emerging equity markets of Central Europe," Journal of Multinational Financial Management, Elsevier, vol. 15(3), pages 287-300, July.
    9. James DiLellio, 2015. "A Kalman filter control technique in mean-variance portfolio management," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(2), pages 235-261, April.
    10. Joëlle Miffre, 2007. "Country-specific ETFs: An efficient approach to global asset allocation," Journal of Asset Management, Palgrave Macmillan, vol. 8(2), pages 112-122, July.
    11. Rudi Schafer & Nils Fredrik Nilsson & Thomas Guhr, 2010. "Power mapping with dynamical adjustment for improved portfolio optimization," Quantitative Finance, Taylor & Francis Journals, vol. 10(1), pages 107-119.
    12. Zymler, Steve & Rustem, Berç & Kuhn, Daniel, 2011. "Robust portfolio optimization with derivative insurance guarantees," European Journal of Operational Research, Elsevier, vol. 210(2), pages 410-424, April.
    13. Hagelin, Niclas & Pramborg, Bengt, 2004. "Dynamic investment strategies with and without emerging equity markets," Emerging Markets Review, Elsevier, vol. 5(2), pages 193-215, June.
    14. Meade, N. & Beasley, J.E. & Adcock, C.J., 2021. "Quantitative portfolio selection: Using density forecasting to find consistent portfolios," European Journal of Operational Research, Elsevier, vol. 288(3), pages 1053-1067.
    15. Füss, Roland & Miebs, Felix & Trübenbach, Fabian, 2014. "A jackknife-type estimator for portfolio revision," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 14-28.
    16. Tze Leung Lai & Haipeng Xing & Zehao Chen, 2011. "Mean--variance portfolio optimization when means and covariances are unknown," Papers 1108.0996, arXiv.org.

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