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Portfolio analysis with DEA: prior to choosing a model

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  • Albane Tarnaud

    (IESEG School of Management)

  • Hervé Leleu

    (CNRS-LEM 9221 and IESEG School of Management)

Abstract

This paper examines the definition of a technology and the choice of a model orientation prior to the analysis of portfolios of financial assets with Data Envelopment Analysis. We acknowledge the previous contributions in the field and provide answers to the questions raised in Cook, Tone & Zhu (2014). These answers allow to determine the purpose of the study and to define the underlying ‘financial’ technology through the identification of the decision-making units and the selection of input and output variables in a multi-moment framework. We also show their impact on the traditional set of axioms that further characterizes the technology and propose some adjustments to the traditional models. We provide illustrations to show the effects of such changes on the scores of technical efficiency and ranking of the portfolios.

Suggested Citation

  • Albane Tarnaud & Hervé Leleu, 2016. "Portfolio analysis with DEA: prior to choosing a model," Working Papers 2016-EQM-05, IESEG School of Management.
  • Handle: RePEc:ies:wpaper:e201605
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    2. Valadkhani, Abbas & Moradi-Motlagh, Amir, 2023. "An empirical analysis of exchange-traded funds in the US," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 995-1009.
    3. Catarina Alexandra Neves Proença & Maria Elisabete Duarte Neves & Maria Castelo Baptista Gouveia & Mara Teresa Silva Madaleno, 2023. "Technological, healthcare and consumer funds efficiency: influence of COVID-19," Operational Research, Springer, vol. 23(2), pages 1-42, June.
    4. Zeng, Ximei & Zhou, Zhongbao & Gong, Yeming & Liu, Wenbin, 2022. "A data envelopment analysis model integrated with portfolio theory for energy mix adjustment: Evidence in the power industry," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    5. Xiao, Helu & Ren, Tiantian & Zhou, Zhongbao & Liu, Wenbin, 2021. "Parameter uncertainty in estimation of portfolio efficiency: Evidence from an interval diversification-consistent DEA approach," Omega, Elsevier, vol. 103(C).
    6. Liu, Yong-Jun & Yang, Guo-Sen & Zhang, Wei-Guo, 2024. "A novel regret-rejoice cross-efficiency approach for energy stock portfolio optimization," Omega, Elsevier, vol. 126(C).
    7. Ioannis E. Tsolas, 2020. "Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach," JRFM, MDPI, vol. 13(5), pages 1-13, April.
    8. Ioannis E. Tsolas, 2020. "The Determinants of the Performance of Precious Metal Mutual Funds," JRFM, MDPI, vol. 13(11), pages 1-10, November.
    9. Adam, Lukáš & Branda, Martin, 2021. "Risk-aversion in data envelopment analysis models with diversification," Omega, Elsevier, vol. 102(C).

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    Keywords

    Data Envelopment Analysis; Portfolio Frontier; Model orientation; Mean-Variance; Risk preferences;
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