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Parameter uncertainty in estimation of portfolio efficiency: Evidence from an interval diversification-consistent DEA approach

Author

Listed:
  • Helu Xiao
  • Tiantian Ren

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Zhongbao Zhou
  • Wenbin Liu

Abstract

Traditional data envelopment analysis (DEA) and diversification-consistent DEA, as the data-driven relative performance evaluation approaches, are widely used in the estimation of portfolio efficiency. To some extent, diversification-consistent DEA is more favored by researchers compared with traditional DEA for it deals fully with portfolio diversification. However, the existing studies assume that decision-makers can accurately estimate the statistical characteristics of portfolio returns and ignore the impact of parameter uncertainty on the portfolio efficiency and its ranking. In this paper, we construct three diversification-consistent DEA models under the mean-variance framework. We treat the expectation and covariance of portfolio return as interval values to characterize the parameter uncertainly in the proposed DEA models. And the bi-level programming models and the corresponding equivalent models are also provided to obtain the lower and upper bounds of portfolio efficiency. We select 30 American industry portfolios and perform some empirical analyses under different datasets to find out which model has better robustness in dealing with the impact of parameter uncertainty on the portfolio efficiency and its ranking. Finally, we provide some robustness tests to further verify the consistency of our findings.

Suggested Citation

  • Helu Xiao & Tiantian Ren & Zhongbao Zhou & Wenbin Liu, 2021. "Parameter uncertainty in estimation of portfolio efficiency: Evidence from an interval diversification-consistent DEA approach," Post-Print hal-03281804, HAL.
    • Handle: RePEc:hal:journl:hal-03281804
    DOI: 10.1016/j.omega.2020.102357
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    Citations

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    Cited by:

    1. Xiao, Helu & Zhou, Zhongbao & Ren, Teng & Liu, Wenbin, 2022. "Estimation of portfolio efficiency in nonconvex settings: A free disposal hull estimator with non-increasing returns to scale," Omega, Elsevier, vol. 111(C).
    2. Abdelouahed Hamdi & Arezou Karimi & Farshid Mehrdoust & Samir Brahim Belhaouari, 2022. "Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms," Mathematics, MDPI, vol. 10(15), pages 1-26, August.
    3. Sehgal, Ruchika & Sharma, Amita & Mansini, Renata, 2023. "Worst-case analysis of Omega-VaR ratio optimization model," Omega, Elsevier, vol. 114(C).
    4. Toloo, Mehdi & Mensah, Emmanuel Kwasi & Salahi, Maziar, 2022. "Robust optimization and its duality in data envelopment analysis," Omega, Elsevier, vol. 108(C).

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