Abstract
This paper proposes a new approach for stock efficiency evaluation based on multiple risk measures. A derived programming model with quadratic constraints is developed based on the envelopment form of data envelopment analysis (DEA). The derived model serves as an input-oriented DEA model by minimizing inputs such as multiple risk measures. In addition, the Russell input measure is introduced and the corresponding efficiency results are evaluated. The findings show that stock efficiency evaluation under the new framework is also effective. The efficiency values indicate that the portfolio frontier under the new framework is more externally enveloped than the DEA efficient surface under the standard DEA framework.
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This paper was supported by the National Natural Science Foundation of China under Grant Nos. 72071192, 71671172, the Anhui Provincial Quality Engineering Teaching and Research Project Under Grant No. 2020jyxm2279, the Anhui University and Enterprise Cooperation Practice Education Base Project under Grant No. 2019sjjd02, Teaching and Research Project of USTC (2019xjyxm019, 2020ycjg08), and the Fundamental Research Funds for the Central Universities (WK2040000027).
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Li, J., Gao, H., Li, Y. et al. Stock Efficiency Evaluation Based on Multiple Risk Measures: A DEA-Like Envelopment Approach. J Syst Sci Complex 35, 1480–1499 (2022). https://doi.org/10.1007/s11424-022-0034-y
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DOI: https://doi.org/10.1007/s11424-022-0034-y