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Portfolio optimization for an investor with a benchmark

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  • R. Korn
  • C. Lindberg

Abstract

The most common equity mandate in the financial industry is to try to outperform an externally given benchmark with known weights. The standard quantitative approach to do this is to optimize the portfolio over short time horizons consecutively, using one-period models. However, it is not clear that this approach actually yields good performance in the long run. We provide a theoretical justification to this methodology by verifying that applying the one-period benchmark-relative mean-variance portfolio, i.e., the industry standard optimal portfolio, continuously is in fact the solution to a specific continuous time portfolio optimization problem: a maximum expected utility problem for an investor who is compared against a benchmark and evaluates her performance based on exponential utility at a deterministic future date. Copyright Springer-Verlag Italia 2014

Suggested Citation

  • R. Korn & C. Lindberg, 2014. "Portfolio optimization for an investor with a benchmark," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 373-384, October.
  • Handle: RePEc:spr:decfin:v:37:y:2014:i:2:p:373-384
    DOI: 10.1007/s10203-013-0148-8
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    References listed on IDEAS

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    1. Stanley R. Pliska, 1986. "A Stochastic Calculus Model of Continuous Trading: Optimal Portfolios," Mathematics of Operations Research, INFORMS, vol. 11(2), pages 371-382, May.
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    Cited by:

    1. Zagst, Rudi & Kraus, Julia & Bertrand, Philippe, 2019. "Option-Based performance participation," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 44-61.
    2. L. Rüschendorf & Steven Vanduffel, 2020. "On the construction of optimal payoffs," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(1), pages 129-153, June.
    3. van Staden, Pieter M. & Forsyth, Peter A. & Li, Yuying, 2024. "Across-time risk-aware strategies for outperforming a benchmark," European Journal of Operational Research, Elsevier, vol. 313(2), pages 776-800.

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