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Portfolio optimization based on downside risk: a mean-semivariance efficient frontier from Dow Jones blue chips

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  • D. Pla-Santamaria
  • M. Bravo

Abstract

To create efficient funds appealing to a sector of bank clients, the objective of minimizing downside risk is relevant to managers of funds offered by the banks. In this paper, a case focusing on this objective is developed. More precisely, the scope and purpose of the paper is to apply the mean-semivariance efficient frontier model, which is a recent approach to portfolio selection of stocks when the investor is especially interested in the constrained minimization of downside risk measured by the portfolio semivariance. Concerning the opportunity set and observation period, the mean-semivariance efficient frontier model is applied to an actual case of portfolio choice from Dow Jones stocks with daily prices observed over the period 2005–2009. From these daily prices, time series of returns (capital gains weekly computed) are obtained as a piece of basic information. Diversification constraints are established so that each portfolio weight cannot exceed 5 per cent. The results show significant differences between the portfolios obtained by mean-semivariance efficient frontier model and those portfolios of equal expected returns obtained by classical Markowitz mean-variance efficient frontier model. Precise comparisons between them are made, leading to the conclusion that the results are consistent with the objective of reflecting downside risk. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • D. Pla-Santamaria & M. Bravo, 2013. "Portfolio optimization based on downside risk: a mean-semivariance efficient frontier from Dow Jones blue chips," Annals of Operations Research, Springer, vol. 205(1), pages 189-201, May.
    • Handle: RePEc:spr:annopr:v:205:y:2013:i:1:p:189-201:10.1007/s10479-012-1243-x
    DOI: 10.1007/s10479-012-1243-x
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    2. Francisco Salas-Molina & Juan A. Rodríguez-Aguilar & David Pla-Santamaria, 2019. "Characterizing compromise solutions for investors with uncertain risk preferences," Operational Research, Springer, vol. 19(3), pages 661-677, September.
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    5. Rutkowska-Ziarko, Anna & Markowski, Lesław & Pyke, Christopher & Amin, Saqib, 2022. "Conventional and downside CAPM: The case of London stock exchange," Global Finance Journal, Elsevier, vol. 54(C).
    6. Hanene Ben Salah & Mohamed Chaouch & Ali Gannoun & Christian Peretti & Abdelwahed Trabelsi, 2018. "Mean and median-based nonparametric estimation of returns in mean-downside risk portfolio frontier," Annals of Operations Research, Springer, vol. 262(2), pages 653-681, March.
    7. Longsheng Cheng & Mahboubeh Shadabfar & Arash Sioofy Khoojine, 2023. "A State-of-the-Art Review of Probabilistic Portfolio Management for Future Stock Markets," Mathematics, MDPI, vol. 11(5), pages 1-34, February.
    8. Garsztka Przemysław & Hołubowicz Krzysztof, 2015. "The Application of Asymmetric Liquidity Risk Measure in Modelling the Risk of Investment," Folia Oeconomica Stetinensia, Sciendo, vol. 15(1), pages 83-100, June.
    9. Ana Garcia-Bernabeu & Antonio Benito & Mila Bravo & David Pla-Santamaria, 2016. "Photovoltaic power plants: a multicriteria approach to investment decisions and a case study in western Spain," Annals of Operations Research, Springer, vol. 245(1), pages 163-175, October.
    10. Duc Hong Vo, 2021. "Portfolio Optimization and Diversification in China: Policy Implications for Vietnam and Other Emerging Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(1), pages 223-238, January.
    11. Hanene Ben Salah & Mohamed Chaouch & Ali Gannoun & Christian Peretti & Abdelwahed Trabelsi, 2018. "Mean and median-based nonparametric estimation of returns in mean-downside risk portfolio frontier," Annals of Operations Research, Springer, vol. 262(2), pages 653-681, March.
    12. Adam Borovička, 2022. "Stock portfolio selection under unstable uncertainty via fuzzy mean-semivariance model," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 595-616, June.
    13. Francisco Salas-Molina & David Pla-Santamaria & Juan A. Rodriguez-Aguilar, 2018. "A multi-objective approach to the cash management problem," Annals of Operations Research, Springer, vol. 267(1), pages 515-529, August.
    14. Anna Rutkowska-Ziarko & Lesław Markowski, 2022. "Accounting and Market Risk Measures of Polish Energy Companies," Energies, MDPI, vol. 15(6), pages 1-21, March.
    15. Amelia Bilbao-Terol & Mar Arenas-Parra & Verónica Cañal-Fernández & Celia Bilbao-Terol, 2016. "Multi-criteria decision making for choosing socially responsible investment within a behavioral portfolio theory framework: a new way of investing into a crisis environment," Annals of Operations Research, Springer, vol. 247(2), pages 549-580, December.
    16. Zheng Gong & Carmine Ventre & John O'Hara, 2021. "The Efficient Hedging Frontier with Deep Neural Networks," Papers 2104.05280, arXiv.org.

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