IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-01404752.html
   My bibliography  Save this paper

Conditional Mean-Variance and Mean-Semivariance models in portfolio optimization

Author

Listed:
  • Hanene Ben Salah

    (Laboratoire BESTMOD ISG Tunis - ISG Tunis, IMAG - Institut Montpelliérain Alexander Grothendieck - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique, SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

  • Ali Gannoun

    (IMAG - Institut Montpelliérain Alexander Grothendieck - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique)

  • Mathieu Ribatet

    (IMAG - Institut Montpelliérain Alexander Grothendieck - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique)

Abstract

It is known that the historical observed returns used to estimate the expected return provide poor guides to predict the future returns. Consequently, the optimal portfolio weights are extremely sensitive to the return assumptions used. Getting information about the future evolution of different asset returns, could help the investors to obtain more efficient portfolio. The solution will be reached by estimating the portfolio risk by conditional variance or conditional semivari-ance. This strategy allows us to take advantage of returns prediction which will be obtained by nonparametric univariate methods. Prediction step uses kernel estimation of conditional mean. Application on the Chinese and the American markets are presented and discussed.

Suggested Citation

  • Hanene Ben Salah & Ali Gannoun & Mathieu Ribatet, 2016. "Conditional Mean-Variance and Mean-Semivariance models in portfolio optimization," Working Papers hal-01404752, HAL.
  • Handle: RePEc:hal:wpaper:hal-01404752
    Note: View the original document on HAL open archive server: https://inria.hal.science/hal-01404752
    as

    Download full text from publisher

    File URL: https://inria.hal.science/hal-01404752/document
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Arditti, Fred D., 1971. "Another Look at Mutual Fund Performance," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 6(3), pages 909-912, June.
    2. Christian de Peretti, 2015. "Median-Based Nonparametric Estimation of Returns in Mean-Down Side Risk Portfolio Frontier," Post-Print hal-02095502, HAL.
    3. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    4. Christian de Peretti, 2015. "A New Approach in Nonparametric Estimation of Returns in Mean-Downside Risk Portfolio frontier," Post-Print hal-02095499, HAL.
    5. Moshe Levy & Richard Roll, 2010. "The Market Portfolio May Be Mean/Variance Efficient After All," The Review of Financial Studies, Society for Financial Studies, vol. 23(6), pages 2464-2491, June.
    6. Chunhachinda, Pornchai & Dandapani, Krishnan & Hamid, Shahid & Prakash, Arun J., 1997. "Portfolio selection and skewness: Evidence from international stock markets," Journal of Banking & Finance, Elsevier, vol. 21(2), pages 143-167, February.
    7. Javier Estrada, 2004. "Mean-Semivariance Behaviour: An Alternative Behavioural Model," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 3(3), pages 231-248, December.
    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. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.

    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. Flores-Ortega, Miguel. & Flores-Castillo, Lilia Alejandra. & Paredes-Gómez, Angelica., 2014. "Selección de portafolios de inversión incluyendo el efecto de asimetría: evidencia con activos de la Bolsa Mexicana de Valores," Panorama Económico, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 0(19), pages 77-101, segundo s.
    2. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Efficient skewness/semivariance portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 331-346, September.
    3. 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.
    4. Paweł Wnuk Lipinski, 2013. "Portfolio selection models based on characteristics of return distributions," Working Papers 2013-14, Faculty of Economic Sciences, University of Warsaw.
    5. Huang, Xiaoxia, 2007. "Two new models for portfolio selection with stochastic returns taking fuzzy information," European Journal of Operational Research, Elsevier, vol. 180(1), pages 396-405, July.
    6. Tee, Kai-Hong, 2009. "The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 303-310, December.
    7. David Chaundy, 1999. "Can Domestic Liabilities Explain the Home Bias in UK Investment Portfolios?," Working Papers wp116, Centre for Business Research, University of Cambridge.
    8. Gourieroux, C. & Monfort, A., 2005. "The econometrics of efficient portfolios," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 1-41, January.
    9. Lu, Xin & Liu, Qiong & Xue, Fengxin, 2019. "Unique closed-form solutions of portfolio selection subject to mean-skewness-normalization constraints," Operations Research Perspectives, Elsevier, vol. 6(C).
    10. Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
    11. Kerstens, Kristiaan & Mounir, Amine & Van de Woestyne, Ignace, 2011. "Geometric representation of the mean-variance-skewness portfolio frontier based upon the shortage function," European Journal of Operational Research, Elsevier, vol. 210(1), pages 81-94, April.
    12. Walter Briec & Kristiaan Kerstens & Octave Jokung, 2007. "Mean-Variance-Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach," Management Science, INFORMS, vol. 53(1), pages 135-149, January.
    13. Arturo Lorenzo Valdés & Antonio Ruiz Porras, 2014. "Un modelo Tgarch con una distribución t de student asimétrica y las hipótesis de racionalidad de los inversionistas bursátiles en Latinoamérica," Archivos Revista Economía y Política., Facultad de Ciencias Económicas y Administrativas, Universidad de Cuenca., vol. 19, pages 66-97, Enero.
    14. Lord Mensah, 2016. "Asset Allocation Brewed Accross African Stock Markets," Proceedings of Economics and Finance Conferences 3205757, International Institute of Social and Economic Sciences.
    15. Chiao, Chaoshin & Hung, Ken & Srivastava, Suresh C., 2003. "Taiwan stock market and four-moment asset pricing model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 13(4), pages 355-381, October.
    16. Ayub, Usman & Shah, Syed Zulfiqar Ali & Abbas, Qaisar, 2015. "Robust analysis for downside risk in portfolio management for a volatile stock market," Economic Modelling, Elsevier, vol. 44(C), pages 86-96.
    17. Richard M. Duvall & Judith L. Quinn, 1981. "Skewness Preference In Stable Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 4(3), pages 249-263, September.
    18. Chunhachinda, Pornchai & Dandapani, Krishnan & Hamid, Shahid & Prakash, Arun J., 1997. "Portfolio selection and skewness: Evidence from international stock markets," Journal of Banking & Finance, Elsevier, vol. 21(2), pages 143-167, February.
    19. Haim Levy & Enrico G. De Giorgi & Thorsten Hens, 2012. "Two Paradigms and Nobel Prizes in Economics: a Contradiction or Coexistence?," European Financial Management, European Financial Management Association, vol. 18(2), pages 163-182, March.
    20. Brandouy, Olivier & Briec, Walter & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2010. "Portfolio performance gauging in discrete time using a Luenberger productivity indicator," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1899-1910, August.

    More about this item

    Keywords

    Conditional Semivariance; DownSide Risk; Conditional Variance; Kernel Method; Nonparametric Mean prediction;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hal:wpaper:hal-01404752. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.