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Journal of Asset Management

, Volume 17, Issue 5, pp 331–346 | Cite as

Efficient skewness/semivariance portfolios

  • Rui Pedro BritoEmail author
  • Hélder Sebastião
  • Pedro Godinho
Original Article

Abstract

This article proposes a flexible methodology for portfolio selection using a skewness/semivariance biobjective optimisation framework. The solutions of this biobjective optimisation problem allow the investor to analyse the efficient trade-off between skewness and semivariance. This methodology is used empirically on four data sets, collected from the Fama/French data library. The out-of-sample performance of the skewness/semivariance model was assessed by choosing three portfolios belonging to each in-sample Pareto frontier and measuring their performance in terms of skewness per semivariance ratio, Sharpe ratio and Sortino ratio. Both the in-sample and the out-of-sample performance analyses were conducted using three different target returns for the semivariance computations. The results show that the efficient skewness/semivariance portfolios are consistently competitive when compared with several benchmark portfolios.

Keywords

portfolio selection semivariance skewness multiobjective optimisation derivative-free optimisation 

Notes

Acknowledgements

The authors thank two anonymous reviewers for their helpful comments. The ‘Notation’ Section, the ‘Benchmark portfolios’ Section and the ‘The skewness/semivariance’ biobjective model’ Section partly overlap a previous paper by Brito and Vicente (2014) (a previous working paper can be found at www.mat.uc.pt/~lnv/papers/cardMV.pdf?). A previous version of this article was published as a working paper by the Group for Monetary and Financial Studies (GEMF). It can be found at www.uc.pt/feuc/gemf/working_papers/pdf/2015/gemf_2015-05.

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Copyright information

© Macmillan Publishers Ltd 2016

Authors and Affiliations

  • Rui Pedro Brito
    • 1
    Email author
  • Hélder Sebastião
    • 1
  • Pedro Godinho
    • 1
  1. 1.University of CoimbraCoimbraPortugal

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