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Risk-aversion in data envelopment analysis models with diversification

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  • Adam, Lukáš
  • Branda, Martin

Abstract

We deal with data envelopment analysis models with diversification which can identify investment opportunities efficient with respect to several inputs and outputs represented by risk and return measures. Moreover, they enable to project the inefficient investment opportunity to the efficient frontier and suggest how to revise its structure. However, the current DEA models does not take into account the individual risk aversion of a particular investor. We will introduce several approaches based on the spectral risk measures which deal with this drawback. These approaches are then compared in the empirical study. Note that all considered models as well as risk aversion are consistent with the second order stochastic dominance.

Suggested Citation

  • Adam, Lukáš & Branda, Martin, 2021. "Risk-aversion in data envelopment analysis models with diversification," Omega, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:jomega:v:102:y:2021:i:c:s0305048320306927
    DOI: 10.1016/j.omega.2020.102338
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    3. Josef Jablonský & Michal Černý & Juraj Pekár, 2022. "The last dozen of years of OR research in Czechia and Slovakia," 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. 30(2), pages 435-447, June.
    4. Yongqiao Wang & He Ni & Stan Uryasev, 2023. "Buffered-ranking intervals for virtual profit efficiency analysis," 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. 31(4), pages 1149-1181, December.

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