IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v262y2018i2d10.1007_s10479-016-2235-z.html
   My bibliography  Save this article

Mean and median-based nonparametric estimation of returns in mean-downside risk portfolio frontier

Author

Listed:
  • Hanene Ben Salah

    (BESTMOD Laboratory
    Université Claude Bernard Lyon 1, Institut de Science Financière et d’Assurances, LSAF EA2429
    IMAG)

  • Mohamed Chaouch

    (United Arab Emirates University)

  • Ali Gannoun

    (IMAG)

  • Christian Peretti

    (Université Claude Bernard Lyon 1, Institut de Science Financière et d’Assurances, LSAF EA2429)

  • Abdelwahed Trabelsi

    (BESTMOD Laboratory)

Abstract

The downside risk (DSR) model for portfolio optimisation allows to overcome the drawbacks of the classical Mean–Variance model concerning the asymmetry of returns and the risk perception of investors. This model optimization deals with a positive definite matrix that is endogenous with respect to portfolio weights. This aspect makes the problem far more difficult to handle. For this purpose, Athayde (2001) developed a new recursive minimization procedure that ensures the convergence to the solution. However, when a finite number of observations is available, the portfolio frontier presents some discontinuity and is not very smooth. In order to overcome that, Athayde (2003) proposed a mean kernel estimation of the returns, so as to create a smoother portfolio frontier. This technique provides an effect similar to the case in which continuous observations are available. In this paper, Athayde model is reformulated and clarified. Then, taking advantage on the robustness of the median, another nonparametric approach based on median kernel returns estimation is proposed in order to construct a portfolio frontier. A new version of Athayde’s algorithm will be exhibited. Finally, the properties of this improved portfolio frontier are studied and analysed on the French Stock Market.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:262:y:2018:i:2:d:10.1007_s10479-016-2235-z
    DOI: 10.1007/s10479-016-2235-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-016-2235-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-016-2235-z?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ang, James S., 1975. "A Note on the E, SL Portfolio Selection Model," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 10(5), pages 849-857, December.
    2. 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.
    3. 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.
    4. Levy, H & Markowtiz, H M, 1979. "Approximating Expected Utility by a Function of Mean and Variance," American Economic Review, American Economic Association, vol. 69(3), pages 308-317, June.
    5. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, 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. Alessia Naccarato & Andrea Pierini & Giovanna Ferraro, 2021. "Markowitz portfolio optimization through pairs trading cointegrated strategy in long-term investment," Annals of Operations Research, Springer, vol. 299(1), pages 81-99, April.
    2. Anna Rutkowska-Ziarko & Lesław Markowski, 2022. "Accounting and Market Risk Measures of Polish Energy Companies," Energies, MDPI, vol. 15(6), pages 1-21, March.
    3. Christian de Peretti, 2015. "A New Approach in Nonparametric Estimation of Returns in Mean-Downside Risk Portfolio frontier," Post-Print hal-02095499, HAL.
    4. Xie, Nan & Wang, Zongrun & Chen, Sicen & Gong, Xu, 2019. "Forecasting downside risk in China’s stock market based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 530-541.
    5. Saker Sabkha & Christian Peretti & Dorra Hmaied, 2019. "On the informational market efficiency of the worldwide sovereign credit default swaps," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 581-608, December.
    6. 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).
    7. Chinnadurai Kathiravan & Murugesan Selvam & Sankaran Venkateswar & S. Balakrishnan, 2021. "Investor behavior and weather factors: evidences from Asian region," Annals of Operations Research, Springer, vol. 299(1), pages 349-373, April.
    8. Fr'ed'eric Butin, 2020. "Generalized distance to a simplex and a new geometrical method for portfolio optimization," Papers 2009.08826, arXiv.org.

    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. 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.
    2. Christian de Peretti, 2015. "A New Approach in Nonparametric Estimation of Returns in Mean-Downside Risk Portfolio frontier," Post-Print hal-02095499, HAL.
    3. Hanene Ben Salah & Ali Gannoun & Christian De Peretti & Mathieu Ribatet & Abdelwahed Trabelsi, 2016. "A New Approach in Nonparametric Estimation of Returns in Mean-DownSide Risk Portfolio frontier," Working Papers hal-01299561, HAL.
    4. Philip A. Horvath & Amit K. Sinha, 2017. "Asymmetric reaction is rational behavior," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(1), pages 160-179, January.
    5. Ricardo Pereira, 2007. "The Cost Of Equity Of Portuguese Public Firms: A Downside Risk Approach," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(1), pages 7-25.
    6. Estrada, Javier, 2007. "Mean-semivariance behavior: Downside risk and capital asset pricing," International Review of Economics & Finance, Elsevier, vol. 16(2), pages 169-185.
    7. repec:spo:wpmain:info:hdl:2441/7182 is not listed on IDEAS
    8. Harding, Don & Pagan, Adrian, 2011. "An Econometric Analysis of Some Models for Constructed Binary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 86-95.
    9. Li, Chenguang & Sexton, Richard J., 2009. "Impacts of Retailers’ Pricing Strategies for Produce Commodities on Farmer Welfare," 2009 Conference, August 16-22, 2009, Beijing, China 51720, International Association of Agricultural Economists.
    10. David Fairris & Gurleen Popli & Eduardo Zepeda, 2008. "Minimum Wages and the Wage Structure in Mexico," Review of Social Economy, Taylor & Francis Journals, vol. 66(2), pages 181-208.
    11. Markowitz, Harry, 2014. "Mean–variance approximations to expected utility," European Journal of Operational Research, Elsevier, vol. 234(2), pages 346-355.
    12. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    13. Joseph G. Altonji & Rosa L. Matzkin, 2001. "Panel Data Estimators for Nonseparable Models with Endogenous Regressors," NBER Technical Working Papers 0267, National Bureau of Economic Research, Inc.
    14. Inanoglu, Hulusi & Jacobs, Michael, Jr. & Liu, Junrong & Sickles, Robin, 2015. "Analyzing Bank Efficiency: Are "Too-Big-to-Fail" Banks Efficient?," Working Papers 15-016, Rice University, Department of Economics.
    15. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    17. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    18. Martins-Filho, Carlos & Yao, Feng & Torero, Maximo, 2018. "Nonparametric Estimation Of Conditional Value-At-Risk And Expected Shortfall Based On Extreme Value Theory," Econometric Theory, Cambridge University Press, vol. 34(1), pages 23-67, February.
    19. Huang, Bai & Lee, Tae-Hwy & Ullah, Aman, 2020. "Combined estimation of semiparametric panel data models," Econometrics and Statistics, Elsevier, vol. 15(C), pages 30-45.
    20. Florencia Gabrielli, 2014. "Econometrics of First Price Auctions: a Survey of the Theoretical and Applied Literature," Económica, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 60, pages 77-118, January-D.
    21. Silva, A. Christian & Prange, Richard E., 2007. "Virtual volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 507-516.

    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:spr:annopr:v:262:y:2018:i:2:d:10.1007_s10479-016-2235-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.