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Portfolio Optimization with Second-Order Stochastic Dominance Constraints and Portfolios Dominating Indices

In: Robustness Analysis in Decision Aiding, Optimization, and Analytics

Author

Listed:
  • Neslihan Fidan Keçeci

    (School of Business, Istanbul University)

  • Viktor Kuzmenko

    (Glushkov Institute of Cybernetics)

  • Stan Uryasev

    (University of Florida)

Abstract

Portfolio optimization models are usually based on several distribution characteristics, such as mean, variance or Conditional Value-at-Risk (CVaR). For instance, the mean-variance approach uses mean and covariance matrix of return of instruments of a portfolio. However this conventional approach ignores tails of return distribution, which may be quite important for the portfolio evaluation. This chapter considers the portfolio optimization problems with the Stochastic Dominance constraints. As a distribution-free decision rule, Stochastic Dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. We implemented efficient numerical algorithms for solving the optimization problems with the Second-Order Stochastic Dominance (SSD) constraints and found portfolios of stocks dominating Dow Jones and DAX indices. We also compared portfolio optimization with SSD constraints with the Minimum Variance and Mean-Variance portfolio optimization.

Suggested Citation

  • Neslihan Fidan Keçeci & Viktor Kuzmenko & Stan Uryasev, 2016. "Portfolio Optimization with Second-Order Stochastic Dominance Constraints and Portfolios Dominating Indices," International Series in Operations Research & Management Science, in: Michael Doumpos & Constantin Zopounidis & Evangelos Grigoroudis (ed.), Robustness Analysis in Decision Aiding, Optimization, and Analytics, chapter 0, pages 285-298, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-33121-8_13
    DOI: 10.1007/978-3-319-33121-8_13
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    Citations

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    Cited by:

    1. Qiuxia Yang, 2020. "Fiscal Transparency and Public Service Quality Association: Evidence from 12 Coastal Provinces and Cities of China," JRFM, MDPI, vol. 14(1), pages 1-14, December.
    2. Runsheng Gu & Lioudmila Vostrikova & Bruno Séjourné, 2020. "Portfolio optimization of euro-denominated funds in French life insurance," Working Papers hal-03025191, HAL.
    3. Neslihan Fidan Keçeci & Yonca Erdem Demirtaş, 2018. "Risk-Based DEA Efficiency and SSD Efficiency of OECD Members Stock Indices," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 6(1), pages 25-36, March.

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