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Efficient Asset Management: A Practical Guide to Stock Portfolio Optimization and Asset Allocation


  • Michaud, Richard O.

    (Acadian Asset Management, Boston)

  • Michaud, Robert O.


In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency(TM) (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz's solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud's new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A final chapter includes practical advice for avoiding simple portfolio design errors. A simple global asset allocation problem illustrates portfolio optimization techniques. The presentation is intuitive, rigorous and informed with institutional management experience to appeal to investment management executives, consultants, fund trustees, brokers, academics, and anyone seeking to stay abreast of the future of investment technology. With its important implications for investment practice, Efficient Asset Management's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.

Suggested Citation

  • Michaud, Richard O. & Michaud, Robert O., 2008. "Efficient Asset Management: A Practical Guide to Stock Portfolio Optimization and Asset Allocation," OUP Catalogue, Oxford University Press, edition 2, number 9780195331912.
  • Handle: RePEc:oxp:obooks:9780195331912

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    References listed on IDEAS

    1. Gordon,Robert J., 2004. "Productivity Growth, Inflation, and Unemployment," Cambridge Books, Cambridge University Press, number 9780521531429, March.
    2. Dale W. Jorgenson, 2001. "Information Technology and the U.S. Economy," American Economic Review, American Economic Association, vol. 91(1), pages 1-32, March.
    3. Gordon,Robert J., 2004. "Productivity Growth, Inflation, and Unemployment," Cambridge Books, Cambridge University Press, number 9780521800082, March.
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    Cited by:

    1. Radovanov Boris & Marcikić Aleksandra, 2014. "Testing The Performance Of The Investment Portfolio Using Block Bootstrap Method," Economic Themes, De Gruyter Open, vol. 52(2), pages 166-183, June.
    2. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.
    3. Billio, Monica & Caporin, Massimiliano & Costola, Michele, 2015. "Backward/forward optimal combination of performance measures for equity screening," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 63-83.
    4. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    5. Zhang, Zhichao & Chau, Frankie & Xie, Li, 2012. "Strategic Asset Allocation for Central Bank’s Management of Foreign Reserves: A new approach," MPRA Paper 43654, University Library of Munich, Germany.
    6. Castro, F. & Gago, J. & Hartillo, I. & Puerto, J. & Ucha, J.M., 2011. "An algebraic approach to integer portfolio problems," European Journal of Operational Research, Elsevier, vol. 210(3), pages 647-659, May.
    7. Qian, Hang, 2011. "Bayesian Portfolio Selection in a Markov Switching Gaussian Mixture Model," MPRA Paper 35561, University Library of Munich, Germany.
    8. Zura Kakushadze & Willie Yu, 2017. "Notes on Fano Ratio and Portfolio Optimization," Papers 1711.10640,
    9. Ban Kawas & Aurelie Thiele, 2017. "Log-robust portfolio management with parameter ambiguity," Computational Management Science, Springer, vol. 14(2), pages 229-256, April.

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