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An enhanced model for portfolio choice with SSD criteria: a constructive approach

Author

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  • Csaba Fábián
  • Gautam Mitra
  • Diana Roman
  • Victor Zverovich

Abstract

We formulate a portfolio planning model that is based on second-order stochastic dominance as the choice criterion. This model is an enhanced version of the multi-objective model proposed by Roman et al. [Math. Progr. Ser. B, 2006, 108, 541–569]; the model compares the scaled values of the different objectives, representing tails at different confidence levels of the resulting distribution. The proposed model can be formulated as a risk minimization model where the objective function is a convex risk measure; we characterize this risk measure and the resulting optimization problem. Moreover, our formulation offers a natural generalization of the SSD-constrained model of Dentcheva and Ruszczyński [J. Bank. Finance, 2006, 30, 433–451]. A cutting plane-based solution method for the proposed model is outlined. We present a computational study showing: (a) the effectiveness of the solution methods and (b) the improved modeling capabilities: the resulting portfolios have superior return distributions.

Suggested Citation

  • Csaba Fábián & Gautam Mitra & Diana Roman & Victor Zverovich, 2011. "An enhanced model for portfolio choice with SSD criteria: a constructive approach," Quantitative Finance, Taylor & Francis Journals, vol. 11(10), pages 1525-1534.
    • Handle: RePEc:taf:quantf:v:11:y:2011:i:10:p:1525-1534
    DOI: 10.1080/14697680903493607
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    Citations

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    1. Malavasi, Matteo & Ortobelli Lozza, Sergio & Trück, Stefan, 2021. "Second order of stochastic dominance efficiency vs mean variance efficiency," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1192-1206.
    2. Csaba Fábián & Krisztián Eretnek & Olga Papp, 2015. "A regularized simplex method," 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. 23(4), pages 877-898, December.
    3. Seyoung Park & Eun Ryung Lee & Sungchul Lee & Geonwoo Kim, 2019. "Dantzig Type Optimization Method with Applications to Portfolio Selection," Sustainability, MDPI, vol. 11(11), pages 1-32, June.
    4. Jianming Xia, 2023. "Benchmark Beating with the Increasing Convex Order," Papers 2311.01692, arXiv.org.
    5. Roman, Diana & Mitra, Gautam & Zverovich, Victor, 2013. "Enhanced indexation based on second-order stochastic dominance," European Journal of Operational Research, Elsevier, vol. 228(1), pages 273-281.
    6. Renato Bruni & Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2012. "A new stochastic dominance approach to enhanced index tracking problems," Economics Bulletin, AccessEcon, vol. 32(4), pages 3460-3470.
    7. Zhidong Bai & Hua Li & Michael McAleer & Wing-Keung Wong, 2015. "Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 889-900, May.
    8. Neslihan Fidan Keçeci & Viktor Kuzmenko & Stan Uryasev, 2016. "Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios," JRFM, MDPI, vol. 9(4), pages 1-14, October.
    9. Bruni, Renato & Cesarone, Francesco & Scozzari, Andrea & Tardella, Fabio, 2017. "On exact and approximate stochastic dominance strategies for portfolio selection," European Journal of Operational Research, Elsevier, vol. 259(1), pages 322-329.
    10. Renato Bruni & Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2012. "A New Lp Model For Enhanced Indexation," Departmental Working Papers of Economics - University 'Roma Tre' 0168, Department of Economics - University Roma Tre.
    11. Nilay Noyan & Gábor Rudolf, 2013. "Optimization with Multivariate Conditional Value-at-Risk Constraints," Operations Research, INFORMS, vol. 61(4), pages 990-1013, August.
    12. Maciej Rysz & Alexander Vinel & Pavlo Krokhmal & Eduardo L. Pasiliao, 2015. "A Scenario Decomposition Algorithm for Stochastic Programming Problems with a Class of Downside Risk Measures," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 416-430, May.
    13. Renato Bruni & Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2013. "No arbitrage and a linear portfolio selection model," Economics Bulletin, AccessEcon, vol. 33(2), pages 1247-1258.
    14. H Mezali & J E Beasley, 2013. "Quantile regression for index tracking and enhanced indexation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(11), pages 1676-1692, November.
    15. Francesco Cesarone & Justo Puerto, 2024. "New approximate stochastic dominance approaches for Enhanced Indexation models," Papers 2401.12669, arXiv.org.
    16. Escudero, Laureano F. & Garín, María Araceli & Merino, María & Pérez, Gloria, 2016. "On time stochastic dominance induced by mixed integer-linear recourse in multistage stochastic programs," European Journal of Operational Research, Elsevier, vol. 249(1), pages 164-176.
    17. Maria Teresa Vespucci & Marida Bertocchi & Laureano F. Escudero & Stefano Zigrino, 2013. "A risk averse stochastic optimization model for power generation capacity expansion," Working Papers (2013-) 1305_qum, University of Bergamo, Department of Management, Economics and Quantitative Methods.

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