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Controlling portfolio skewness and kurtosis without directly optimizing third and fourth moments

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  • Kim, Woo Chang
  • Fabozzi, Frank J.
  • Cheridito, Patrick
  • Fox, Charles

Abstract

In spite of their importance, third or higher moments of portfolio returns are often neglected in portfolio construction problems due to the computational difficulties associated with them. In this paper, we propose a new robust mean–variance approach that can control portfolio skewness and kurtosis without imposing higher moment terms. The key idea is that, if the uncertainty sets are properly constructed, robust portfolios based on the worst-case approach within the mean–variance setting favor skewness and penalize kurtosis.

Suggested Citation

  • Kim, Woo Chang & Fabozzi, Frank J. & Cheridito, Patrick & Fox, Charles, 2014. "Controlling portfolio skewness and kurtosis without directly optimizing third and fourth moments," Economics Letters, Elsevier, vol. 122(2), pages 154-158.
    • Handle: RePEc:eee:ecolet:v:122:y:2014:i:2:p:154-158
    DOI: 10.1016/j.econlet.2013.11.024
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    Cited by:

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    3. Marie-Hélène Broihanne & Maxime Merli & Patrick Roger, 2016. "Diversification, gambling and market forces," Review of Quantitative Finance and Accounting, Springer, vol. 47(1), pages 129-157, July.
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    6. Khashanah, Khaldoun & Simaan, Majeed & Simaan, Yusif, 2022. "Do we need higher-order comoments to enhance mean-variance portfolios? Evidence from a simplified jump process," International Review of Financial Analysis, Elsevier, vol. 81(C).
    7. Ñíguez, Trino-Manuel & Paya, Ivan & Peel, David, 2016. "Pure higher-order effects in the portfolio choice model," Finance Research Letters, Elsevier, vol. 19(C), pages 255-260.
    8. Massimiliano Kaucic & Filippo Piccotto & Gabriele Sbaiz, 2024. "A constrained swarm optimization algorithm for large-scale long-run investments using Sharpe ratio-based performance measures," Computational Management Science, Springer, vol. 21(1), pages 1-29, June.
    9. Wei-Bin Zhang, 2017. "Discrimination and Inequality in an Integrated Walrasian-General-Equilibrium and Neoclassical-Growth Theory," Asian Journal of Economic Modelling, Asian Economic and Social Society, vol. 5(1), pages 57-76, March.
    10. 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.
    11. Pavlo Dziuba & Olena Pryiatelchuk & Denys Rusak, 2021. "Equity Markets Risks And Returns: Implications For Global Portfolio Capital Flows During Pandemic And Crisis Periods," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 7(3).
    12. Linda Chamakh & Zoltan Szabo, 2021. "Keep it Tighter -- A Story on Analytical Mean Embeddings," Papers 2110.09516, arXiv.org, revised Nov 2024.
    13. Salo, Ahti & Doumpos, Michalis & Liesiö, Juuso & Zopounidis, Constantin, 2024. "Fifty years of portfolio optimization," European Journal of Operational Research, Elsevier, vol. 318(1), pages 1-18.
    14. Chamakh, Linda & Szabo, Zoltan, 2021. "Keep it tighter -- A story on analytical mean embeddings," LSE Research Online Documents on Economics 115723, London School of Economics and Political Science, LSE Library.
    15. Bouri, Elie, 2023. "Spillovers in the joint system of conditional higher-order moments: US evidence from green energy, brown energy, and technology stocks," Renewable Energy, Elsevier, vol. 210(C), pages 507-523.
    16. 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).
    17. Wang, Yihan & Goutte, Stephane & Bouri, Elie & Sokhanvar, Amin, 2024. "Climate risks and the realized higher-order moments of financial markets: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 1064-1087.
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    More about this item

    Keywords

    Portfolio selection; Robust portfolio; Higher moments; Mean–variance framework;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

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