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Novel approaches for portfolio construction using second order stochastic dominance

Author

Listed:
  • Cristiano Arbex Valle

    (Optirisk Systems)

  • Diana Roman

    (Brunel University)

  • Gautam Mitra

    (Optirisk Systems
    University College London (UCL))

Abstract

In the last decade, a few models of portfolio construction have been proposed which apply second order stochastic dominance (SSD) as a choice criterion. SSD approach requires the use of a reference distribution which acts as a benchmark. The return distribution of the computed portfolio dominates the benchmark by the SSD criterion. The benchmark distribution naturally plays an important role since different benchmarks lead to very different portfolio solutions. In this paper we describe a novel concept of reshaping the benchmark distribution with a view to obtaining portfolio solutions which have enhanced return distributions. The return distribution of the constructed portfolio is considered enhanced if the left tail is improved, the downside risk is reduced and the standard deviation remains within a specified range. We extend this approach from long only to long-short strategies which are used by many hedge fund and quant fund practitioners. We present computational results which illustrate (1) how this approach leads to superior portfolio performance (2) how significantly better performance is achieved for portfolios that include shorting of assets.

Suggested Citation

  • Cristiano Arbex Valle & Diana Roman & Gautam Mitra, 2017. "Novel approaches for portfolio construction using second order stochastic dominance," Computational Management Science, Springer, vol. 14(2), pages 257-280, April.
    • Handle: RePEc:spr:comgts:v:14:y:2017:i:2:d:10.1007_s10287-017-0274-9
    DOI: 10.1007/s10287-017-0274-9
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Cristiano Arbex Valle, 2024. "Portfolio optimisation: bridging the gap between theory and practice," Papers 2407.00887, arXiv.org, revised Sep 2024.
    2. Giorgio Consigli & Vittorio Moriggia & Sebastiano Vitali, 2020. "Long-term individual financial planning under stochastic dominance constraints," Annals of Operations Research, Springer, vol. 292(2), pages 973-1000, September.
    3. 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.
    4. Francesco Cesarone & Raffaello Cesetti & Giuseppe Orlando & Manuel Luis Martino & Jacopo Maria Ricci, 2022. "Comparing SSD-Efficient Portfolios with a Skewed Reference Distribution," Mathematics, MDPI, vol. 11(1), pages 1-20, December.
    5. Cristiano Arbex Valle & John E Beasley & Nigel Meade, 2024. "Subset second-order stochastic dominance for enhanced indexation with diversification enforced by sector constraints," Papers 2404.16777, arXiv.org, revised Nov 2024.
    6. Francesco Cesarone & Justo Puerto, 2024. "New approximate stochastic dominance approaches for Enhanced Indexation models," Papers 2401.12669, arXiv.org.

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