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A Strategy Which Maximizes the Geometric Mean Return on Portfolio Investments

Author

Listed:
  • James H. Vander Weide

    (Duke University)

  • David W. Peterson

    (Duke University)

  • Steven F. Maier

    (Duke University)

Abstract

A common formulation of the portfolio selection problem leads to the prescription of a strategy which maximizes the geometric mean return on investments. In this paper we examine conditions under which solutions exist for the case where the returns distribution is discrete. We establish necessary and sufficient conditions for a solution to exist and give a computationally convenient and exact method for finding a solution in circumstances where (i) a solution exists and (ii) the number of securities equals or exceeds the number of values in the returns distribution.

Suggested Citation

  • James H. Vander Weide & David W. Peterson & Steven F. Maier, 1977. "A Strategy Which Maximizes the Geometric Mean Return on Portfolio Investments," Management Science, INFORMS, vol. 23(10), pages 1117-1123, June.
    • Handle: RePEc:inm:ormnsc:v:23:y:1977:i:10:p:1117-1123
    DOI: 10.1287/mnsc.23.10.1117
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    Cited by:

    1. Helena Jasiulewicz & Wojciech Kordecki, 2016. "Multiplicative parameters and estimators: applications in economics and finance," Annals of Operations Research, Springer, vol. 238(1), pages 299-313, March.
    2. Sonntag, Dominik, 2018. "Die Theorie der fairen geometrischen Rendite [The Theory of Fair Geometric Returns]," MPRA Paper 87082, University Library of Munich, Germany.
    3. Locatelli, Giorgio & Mancini, Mauro, 2011. "Large and small baseload power plants: Drivers to define the optimal portfolios," Energy Policy, Elsevier, vol. 39(12), pages 7762-7775.
    4. Muteba Mwamba, John & Suteni, Mwambi, 2010. "An alternative to portfolio selection problem beyond Markowitz’s: Log Optimal Growth Portfolio," MPRA Paper 50240, University Library of Munich, Germany.
    5. Helena Jasiulewicz & Wojciech Kordecki, 2016. "Multiplicative parameters and estimators: applications in economics and finance," Annals of Operations Research, Springer, vol. 238(1), pages 299-313, March.

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