IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v122y2014i2p154-158.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176513005181
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2013.11.024?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Louis Eeckhoudt & Harris Schlesinger, 2006. "Putting Risk in Its Proper Place," American Economic Review, American Economic Association, vol. 96(1), pages 280-289, March.
    2. A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
    3. Xiao Qin, 2012. "Can L-moments beat central moments in modelling risk? An empirical analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1441-1447, October.
    4. Ghislain Yanou, 2013. "Extension of the random matrix theory to the L-moments for robust portfolio selection," Quantitative Finance, Taylor & Francis Journals, vol. 13(10), pages 1653-1673, October.
    5. Zhang, Lingyun, 2007. "Sample Mean and Sample Variance: Their Covariance and Their (In)Dependence," The American Statistician, American Statistical Association, vol. 61, pages 159-160, May.
    6. Darolles, Serge & Gourieroux, Christian & Jasiak, Joann, 2009. "L-performance with an application to hedge funds," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 671-685, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Douadia Bougherara & Laurent Piet, 2018. "On the role of probability weighting on WTP for crop insurance with and without yield skewness," Working Papers hal-02790605, HAL.
    2. Fredy Pokou & Jules Sadefo Kamdem & François Benhmad, 2024. "Empirical Performance of an ESG Assets Portfolio from US Market," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1569-1638, September.
    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.
    4. 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.
    5. 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.
    6. 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.
    7. Lassance, Nathan & Vrins, Frédéric, 2023. "Portfolio selection: A target-distribution approach," European Journal of Operational Research, Elsevier, vol. 310(1), pages 302-314.
    8. Bouri, Elie & Gupta, Rangan & Pierdzioch, Christian & Polat, Onur, 2024. "Forecasting U.S. recessions using over 150 years of data: Stock-market moments versus oil-market moments," Finance Research Letters, Elsevier, vol. 69(PB).
    9. 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).
    10. Nekhili, Ramzi & Bouri, Elie, 2023. "Higher-order moments and co-moments' contribution to spillover analysis and portfolio risk management," Energy Economics, Elsevier, vol. 119(C).
    11. Deng Xiong & Liu Yanli, 2018. "A High-Moment Trapezoidal Fuzzy Random Portfolio Model with Background Risk," Journal of Systems Science and Information, De Gruyter, vol. 6(1), pages 1-28, February.
    12. 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).
    13. 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.
    14. 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).
    15. Linda Chamakh & Zoltan Szabo, 2021. "Keep it Tighter -- A Story on Analytical Mean Embeddings," Papers 2110.09516, arXiv.org, revised Nov 2024.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. Adler Haymans MANURUNG & Fadh Fauzi HIBATULLAH & Jadongan SIJABAT, 2023. "Stock Selection Using Roy Criteria to Construct a Portfolio and the Effects of Variables on Portfolio Return," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 12(3), pages 1-2.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Olivier Courtois & Xia Xu, 2024. "Efficient portfolios and extreme risks: a Pareto–Dirichlet approach," Annals of Operations Research, Springer, vol. 335(1), pages 261-292, April.
    2. Ren, Tiantian & Kerstens, Kristiaan & Kumar, Saurav, 2024. "Risk-aversion versus risk-loving preferences in nonparametric frontier-based fund ratings: A buy-and-hold backtesting strategy," European Journal of Operational Research, Elsevier, vol. 319(1), pages 332-344.
    3. Monica Billio & Bertrand Maillet & Loriana Pelizzon, 2022. "A meta-measure of performance related to both investors and investments characteristics," Annals of Operations Research, Springer, vol. 313(2), pages 1405-1447, June.
    4. Eeckhoudt, Louis & Schlesinger, Harris, 2008. "Changes in risk and the demand for saving," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1329-1336, October.
    5. Marco Minozzo & Luca Bagnato, 2021. "A unified skew‐normal geostatistical factor model," Environmetrics, John Wiley & Sons, Ltd., vol. 32(4), June.
    6. Bernardi, Mauro, 2013. "Risk measures for skew normal mixtures," Statistics & Probability Letters, Elsevier, vol. 83(8), pages 1819-1824.
    7. repec:dau:papers:123456789/11094 is not listed on IDEAS
    8. Claudio A. Bonilla & Pablo A. Gutiérrez Cubillos, 2021. "The effects of ambiguity on entrepreneurship," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 30(1), pages 63-80, February.
    9. Michel M. Denuit & Louis Eeckhoudt, 2010. "A General Index of Absolute Risk Attitude," Management Science, INFORMS, vol. 56(4), pages 712-715, April.
    10. Denuit, Michel M. & Eeckhoudt, Louis & Schlesinger, Harris, 2013. "When Ross meets Bell: The linex utility function," Journal of Mathematical Economics, Elsevier, vol. 49(2), pages 177-182.
    11. Courbage, Christophe & Rey, Béatrice, 2012. "Priority setting in health care and higher order degree change in risk," Journal of Health Economics, Elsevier, vol. 31(3), pages 484-489.
    12. Reinaldo B. Arellano-Valle & Marc G. Genton, 2010. "Multivariate extended skew-t distributions and related families," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 201-234.
    13. Lachos, Victor H. & Prates, Marcos O. & Dey, Dipak K., 2021. "Heckman selection-t model: Parameter estimation via the EM-algorithm," Journal of Multivariate Analysis, Elsevier, vol. 184(C).
    14. López-Díaz, Miguel & Sordo, Miguel A. & Suárez-Llorens, Alfonso, 2012. "On the Lp-metric between a probability distribution and its distortion," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 257-264.
    15. Gollier, Christian, 2021. "A general theory of risk apportionment," Journal of Economic Theory, Elsevier, vol. 192(C).
    16. Firpo, Sergio & Galvao, Antonio F. & Kobus, Martyna & Parker, Thomas & Rosa-Dias, Pedro, 2020. "Loss Aversion and the Welfare Ranking of Policy Interventions," IZA Discussion Papers 13176, Institute of Labor Economics (IZA).
    17. Fang, B.Q., 2006. "Sample mean, covariance and T2 statistic of the skew elliptical model," Journal of Multivariate Analysis, Elsevier, vol. 97(7), pages 1675-1690, August.
    18. Massimo Bilancia & Giacomo Demarinis, 2014. "Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA)," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 71-94, March.
    19. Eeckhoudt, Louis & Schlesinger, Harris, 2009. "On the utility premium of Friedman and Savage," Economics Letters, Elsevier, vol. 105(1), pages 46-48, October.
    20. Bi, Hongwei & Huang, Rachel J. & Tzeng, Larry Y. & Zhu, Wei, 2019. "Higher-order Omega: A performance index with a decision-theoretic foundation," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 43-57.
    21. Kerstens, Kristiaan & Mounir, Amine & de Woestyne, Ignace Van, 2011. "Non-parametric frontier estimates of mutual fund performance using C- and L-moments: Some specification tests," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1190-1201, May.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:122:y:2014:i:2:p:154-158. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.