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Evaluating the impact of inequality constraints and parameter uncertainty on optimal portfolio choice

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  • A. D. Hall
  • S. E. Satchell
  • P. J. Spence

Abstract

We present new analytical results for the impact of portfolio weight constraints on an investor's optimal portfolio when parameter uncertainty is taken into account. While it is well known that parameter uncertainty and imposing weight constraints results in reduced certainty equivalent returns, in the general case, there are no analytical results. In a special case, commonly used in the funds management literature, we derive analytical expression for the certainty equivalent loss that does not depend on the risk aversion parameter. We illustrate our theoretical results using hedge fund data, from the perspective of a fund-of-fund manager. Our contribution is to formalize the framework to investigate this problem, as well as providing tractable analytical solutions that can be implemented using either simulated or asset manager returns.

Suggested Citation

  • A. D. Hall & S. E. Satchell & P. J. Spence, 2015. "Evaluating the impact of inequality constraints and parameter uncertainty on optimal portfolio choice," Applied Economics, Taylor & Francis Journals, vol. 47(45), pages 4801-4813, September.
    • Handle: RePEc:taf:applec:v:47:y:2015:i:45:p:4801-4813
    DOI: 10.1080/00036846.2015.1034845
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    References listed on IDEAS

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    1. Kan, Raymond & Zhou, Guofu, 2007. "Optimal Portfolio Choice with Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(3), pages 621-656, September.
    2. Bengtsson, Christoffer, 2003. "The Impact of Estimation Error on Portfolio Selection for Investors with Constant Relative Risk Aversion," Working Papers 2003:17, Lund University, Department of Economics, revised 29 Apr 2004.
    3. J. Knight & S. E. Satchell, 2010. "Exact properties of measures of optimal investment for benchmarked portfolios," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 495-502.
    4. Best, Michael J & Grauer, Robert R, 1991. "On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results," Review of Financial Studies, Society for Financial Studies, vol. 4(2), pages 315-342.
    5. Fung, William & Hsieh, David A, 2001. "The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers," Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 313-341.
    6. Treynor, Jack L & Black, Fischer, 1973. "How to Use Security Analysis to Improve Portfolio Selection," The Journal of Business, University of Chicago Press, vol. 46(1), pages 66-86, January.
    7. 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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