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Portfolio selection with skewness : a comparison of methods and a generalized one fund result

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  • W. Briec
  • K. Kerstens

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

  • I. van de Woestyne

Abstract

This contribution compares existing and newly developed techniques for geometrically representing mean-variance-skewness portfolio frontiers based on the rather widely adapted methodology of polynomial goal programming (PGP) on the one hand and the more recent approach based on the shortage function on the other hand. Moreover, we explain the working of these different methodologies in detail and provide graphical illustrations in relation to the goal programming literature in operations research. Inspired by these illustrations, we prove two new results: a formal relation between both approaches and a generalization of the well-known one fund separation theorem from traditional mean-variance portfolio theory.
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  • W. Briec & K. Kerstens & I. van de Woestyne, 2013. "Portfolio selection with skewness : a comparison of methods and a generalized one fund result," Post-Print hal-00837674, HAL.
    • Handle: RePEc:hal:journl:hal-00837674
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    Cited by:

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    2. Farshad Noravesh & Kristiaan Kerstens, 2022. "Some connections between higher moments portfolio optimization methods," Papers 2201.00205, arXiv.org.
    3. 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).
    4. Lassance, Nathan, 2022. "Reconciling mean-variance portfolio theory with non-Gaussian returns," European Journal of Operational Research, Elsevier, vol. 297(2), pages 729-740.
    5. Andreu, Laura & Serrano, Miguel & Vicente, Luis, 2019. "Efficiency of mutual fund managers: A slacks-based manager efficiency index," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1180-1193.
    6. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.
    7. 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.
    8. Adrian Gepp & Geoff Harris & Bruce Vanstone, 2020. "Financial applications of semidefinite programming: a review and call for interdisciplinary research," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(4), pages 3527-3555, December.
    9. Mellios, Constantin & Six, Pierre & Lai, Anh Ngoc, 2016. "Dynamic speculation and hedging in commodity futures markets with a stochastic convenience yield," European Journal of Operational Research, Elsevier, vol. 250(2), pages 493-504.
    10. Dong, Xiaohui & Wang, Ming & Zhong, Guang-Yan & Yang, Fengzao & Duan, Weilong & Li, Jiang-Cheng & Xiong, Kezhao & Zeng, Chunhua, 2018. "Stochastic delayed kinetics of foraging colony system under non-Gaussian noise," Chaos, Solitons & Fractals, Elsevier, vol. 112(C), pages 1-13.
    11. Lassance, Nathan & Vrins, Frédéric, 2019. "Robust portfolio selection using sparse estimation of comoment tensors," LIDAM Discussion Papers LFIN 2019007, Université catholique de Louvain, Louvain Finance (LFIN).
    12. Lassance, Nathan & Vrins, Frédéric, 2021. "Portfolio selection with parsimonious higher comoments estimation," Journal of Banking & Finance, Elsevier, vol. 126(C).
    13. Vohra, Suprita & Fabozzi, Frank J., 2019. "Effectiveness of developed and emerging market FX options in active currency risk management," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 130-146.
    14. Massimiliano Kaucic & Roberto Daris, 2015. "Multi-Objective Stochastic Optimization Programs for a Non-Life Insurance Company under Solvency Constraints," Risks, MDPI, vol. 3(3), pages 1-30, September.

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    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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