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Robust Portfolio Optimisation with Specified Competitors

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Listed:
  • Gonc{c}alo Sim~oes
  • Mark McDonald
  • Stacy Williams
  • Daniel Fenn
  • Raphael Hauser

Abstract

We extend Relative Robust Portfolio Optimisation models to allow portfolios to optimise their distance to a set of benchmarks. Portfolio managers are also given the option of computing regret in a way which is more in line with market practices than other approaches suggested in the literature. In addition, they are given the choice of simply adding an extra constraint to their optimisation problem instead of outright changing the objective function, as is commonly suggested in the literature. We illustrate the benefits of this approach by applying it to equity portfolios in a variety of regions.

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  • Gonc{c}alo Sim~oes & Mark McDonald & Stacy Williams & Daniel Fenn & Raphael Hauser, 2017. "Robust Portfolio Optimisation with Specified Competitors," Papers 1701.02958, arXiv.org.
    • Handle: RePEc:arx:papers:1701.02958
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    3. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
    4. Raphael Hauser & Vijay Krishnamurthy & Reha Tutuncu, 2013. "Relative Robust Portfolio Optimization," Papers 1305.0144, arXiv.org, revised May 2013.
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