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A multicriteria model for portfolio management

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Listed:
  • Carlos Bana
  • E. Costa
  • Joao Oliveira Soares

Abstract

The paper presents a new model to support the selection of a portfolio of stocks based on the results of the fieldwork undertaken with fund managers and using direct rating, MACBETH and optimisation techniques. The model consists of defining a benchmark portfolio (in this case, the Dow Jones Eurostoxx50) and scoring its different stocks according to several expected return criteria. Based on this multicriteria value analysis, a procedure is proposed to suggest adjustments to the proportions of the stocks in the portfolio. Finally, the risk of this modified portfolio is taken into consideration in an optimization module that includes constraints concerning the limits of variation for the proportion of each stock.

Suggested Citation

  • Carlos Bana & E. Costa & Joao Oliveira Soares, 2004. "A multicriteria model for portfolio management," The European Journal of Finance, Taylor & Francis Journals, vol. 10(3), pages 198-211.
    • Handle: RePEc:taf:eurjfi:v:10:y:2004:i:3:p:198-211
    DOI: 10.1080/1351847032000113254
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    References listed on IDEAS

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    1. Haugen, Robert A. & Baker, Nardin L., 1996. "Commonality in the determinants of expected stock returns," Journal of Financial Economics, Elsevier, vol. 41(3), pages 401-439, July.
    2. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
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    Cited by:

    1. Hirschberger, Markus & Qi, Yue & Steuer, Ralph E., 2010. "Large-scale MV efficient frontier computation via a procedure of parametric quadratic programming," European Journal of Operational Research, Elsevier, vol. 204(3), pages 581-588, August.
    2. P Xidonas & G Mavrotas & J Psarras, 2010. "A multiple criteria decision-making approach for the selection of stocks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(8), pages 1273-1287, August.
    3. Murat Köksalan & Ceren Tuncer Şakar, 2016. "An interactive approach to stochastic programming-based portfolio optimization," Annals of Operations Research, Springer, vol. 245(1), pages 47-66, October.
    4. James DiLellio, 2015. "A Kalman filter control technique in mean-variance portfolio management," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(2), pages 235-261, April.
    5. Florian Methling & Rüdiger Nitzsch, 2019. "Thematic portfolio optimization: challenging the core satellite approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 133-154, June.
    6. Constantin Zopounidis & Michael Doumpos, 2013. "Multicriteria decision systems for financial problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 241-261, July.
    7. Panagiotis Xidonas & George Mavrotas & John Psarras, 2010. "Equity portfolio construction and selection using multiobjective mathematical programming," Journal of Global Optimization, Springer, vol. 47(2), pages 185-209, June.
    8. Hirschberger, Markus & Qi, Yue & Steuer, Ralph E., 2007. "Randomly generating portfolio-selection covariance matrices with specified distributional characteristics," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1610-1625, March.
    9. Bruce Burton & Satish Kumar & Nitesh Pandey, 2020. "Twenty-five years of The European Journal of Finance (EJF): a retrospective analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 26(18), pages 1817-1841, December.

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