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Geometric Representation of the Mean-Variance-Skewness Porfolio Frontier Based upon the Shortage Function

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  • K. Kerstens

    (LEM - Lille - Economie et Management - Université de Lille, Sciences et Technologies - CNRS - Centre National de la Recherche Scientifique)

Abstract

The literature suggests that investors prefer portfolios based on mean, variance and skewness rather than portfolios based on mean-variance (MV) criteria solely. Furthermore, a small variety of methods have been proposed to determine mean-variance-skewness (MVS) optimal portfolios. Recently, the shortage function has been introduced as a measure of efficiency, allowing to characterize MVS optimalportfolios using non-parametric mathematical programming tools. While tracing the MV portfolio frontier has become trivial, the geometric representation of the MVS frontier is an open challenge. A hitherto unnoticed advantage of the shortage function is that it allows to geometrically represent the MVS portfolio frontier. The purpose of this contribution is to systematically develop geometric representations of the MVS portfolio frontier using the shortage function and related approaches.
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  • K. Kerstens, 2007. "Geometric Representation of the Mean-Variance-Skewness Porfolio Frontier Based upon the Shortage Function," Post-Print hal-00288790, HAL.
    • Handle: RePEc:hal:journl:hal-00288790
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    3. Xiao, Helu & Zhou, Zhongbao & Ren, Teng & Liu, Wenbin, 2022. "Estimation of portfolio efficiency in nonconvex settings: A free disposal hull estimator with non-increasing returns to scale," Omega, Elsevier, vol. 111(C).
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    5. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    6. Zhou, Zhongbao & Jin, Qianying & Xiao, Helu & Wu, Qian & Liu, Wenbin, 2018. "Estimation of cardinality constrained portfolio efficiency via segmented DEA," Omega, Elsevier, vol. 76(C), pages 28-37.
    7. Harris, Richard D.F. & Stoja, Evarist & Tan, Linzhi, 2017. "The dynamic Black–Litterman approach to asset allocation," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1085-1096.
    8. K. Saranya & P. Prasanna, 2014. "Portfolio Selection and Optimization with Higher Moments: Evidence from the Indian Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 21(2), pages 133-149, May.
    9. Nalpas, Nicolas & Simar, Leopold & Vanhems, Anne, 2016. "Portfolio Selection in a Multi-Input Multi-Output Setting:a Simple Monte-Carlo-FDH Algorithm," LIDAM Discussion Papers ISBA 2016022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Chang, Tzu-Pu & Hu, Jin-Li & Chou, Ray Yeutien & Sun, Lei, 2012. "The sources of bank productivity growth in China during 2002–2009: A disaggregation view," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1997-2006.
    11. Brandouy, Olivier & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2009. "Exploring Bi-Criteria versus Multi-Dimensional Lower Partial Moment Portfolio Models," Working Papers 2009/29, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    12. Lord Mensah, 2016. "Asset Allocation Brewed Accross African Stock Markets," Proceedings of Economics and Finance Conferences 3205757, International Institute of Social and Economic Sciences.
    13. Jens J. Krüger, 2021. "Nonparametric portfolio efficiency measurement with higher moments," Empirical Economics, Springer, vol. 61(3), pages 1435-1459, September.
    14. Valeria V. Lakshina, 2019. "Do Portfolio Investors Need To Consider The Asymmetry Of Returns On The Russian Stock Market?," HSE Working papers WP BRP 75/FE/2019, National Research University Higher School of Economics.
    15. Krüger, Jens J., 2021. "Nonparametric portfolio efficiency measurement with higher moments," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 130825, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    16. Brandouy, Olivier & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2015. "Frontier-based vs. traditional mutual fund ratings: A first backtesting analysis," European Journal of Operational Research, Elsevier, vol. 242(1), pages 332-342.
    17. Aparicio, Juan & Mahlberg, Bernhard & Pastor, Jesus T. & Sahoo, Biresh K., 2014. "Decomposing technical inefficiency using the principle of least action," European Journal of Operational Research, Elsevier, vol. 239(3), pages 776-785.
    18. Adam, Lukáš & Branda, Martin, 2021. "Risk-aversion in data envelopment analysis models with diversification," Omega, Elsevier, vol. 102(C).
    19. Branda, Martin, 2015. "Diversification-consistent data envelopment analysis based on directional-distance measures," Omega, Elsevier, vol. 52(C), pages 65-76.
    20. Emmanuel Jurczenko & Bertrand Maillet & Paul Merlin, 2008. "Efficient Frontier for Robust Higher-order Moment Portfolio Selection," Post-Print halshs-00336475, HAL.
    21. Briec, Walter & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2011. "Portfolio Selection with Skewness: A Comparison and a Generalized Two Fund Separation Result," Working Papers 2011/09, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    22. Lakshina, Valeriya, 2020. "Do portfolio investors need to consider the asymmetry of returns on the Russian stock market?," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    23. Krüger, Jens J., 2024. "Nonparametric portfolio efficiency measurement with higher moments," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 144371, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    24. Goh, Joel Weiqiang & Lim, Kian Guan & Sim, Melvyn & Zhang, Weina, 2012. "Portfolio value-at-risk optimization for asymmetrically distributed asset returns," European Journal of Operational Research, Elsevier, vol. 221(2), pages 397-406.

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