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Geometrical framework for robust portfolio optimization

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  • Bazovkin, Pavel

Abstract

We consider a vector-valued multivariate risk measure that depends on the user's profile given by the user's utility. It is constructed on the basis of weighted-mean trimmed regions and represents the solution of an optimization problem. The key feature of this measure is convexity. We apply the measure to the portfolio selection problem, employing different measures of performance as objective functions in a common geometrical framework.

Suggested Citation

  • Bazovkin, Pavel, 2014. "Geometrical framework for robust portfolio optimization," Discussion Papers in Econometrics and Statistics 01/14, University of Cologne, Institute of Econometrics and Statistics.
    • Handle: RePEc:zbw:ucdpse:0114
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    File URL: https://www.econstor.eu/bitstream/10419/102645/1/797490663.pdf
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    References listed on IDEAS

    as
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    Cited by:

    1. Pavel Bazovkin & Karl Mosler, 2015. "A general solution for robust linear programs with distortion risk constraints," Annals of Operations Research, Springer, vol. 229(1), pages 103-120, June.

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    More about this item

    Keywords

    Multivariate risk measure; robust portfolio optimization; weighted-mean trimmed regions; data central regions; convex risk measure; distortion risk measure;
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