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The trade-off frontier for ESG and Sharpe ratio: a bootstrapped double-frontier data envelopment analysis

Author

Listed:
  • Sabri Boubaker

    (EM Normandie Business School, Métis Lab
    International School, Vietnam National University
    Swansea University)

  • Tu D. Q. Le

    (University of Economics and Law
    Vietnam National University)

  • Riadh Manita

    (NEOMA Business School)

  • Thanh Ngo

    (School of Aviation, Massey University
    VNU University of Economics and Business)

Abstract

The trade-off between the returns and the risks associated with the stocks (i.e., the Sharpe ratio, SR) is an important measure of portfolio optimization. In recent years, the environmental, social, and governance (ESG) has increasingly proven its influence on stocks’ returns, resulting in the evolvement from a two-dimensional (i.e., risks versus returns) into a multi-dimensional setting (e.g., risks versus returns versus ESG). This study is the first to examine this setting in the global energy sector using a (slacks-based measures, SBM) ESG-SR double-frontier double-bootstrap (ESG-SR DFDB) by studying the determinants of the overall ESG-SR efficiency for 334 energy firms from 45 countries in 2019. We show that only around 11% of our sampled firms perform well in the multi-dimensional ESG-SR efficient frontier. The 2019 average (in)efficiency of the global energy sector was 2.273, given an efficient level of 1.000. Besides the differences in the firm’s input/output utilization (regarding their E, S, G, and SR values), we found that the firm- (e.g., market capitalization and board characteristics) and country-level characteristics (e.g., the rule of law) have positive impacts on their ESG-SR performance. Such findings, therefore, are essential not only to the (responsible) investors but also to managers and policymakers in those firms/countries.

Suggested Citation

  • Sabri Boubaker & Tu D. Q. Le & Riadh Manita & Thanh Ngo, 2025. "The trade-off frontier for ESG and Sharpe ratio: a bootstrapped double-frontier data envelopment analysis," Annals of Operations Research, Springer, vol. 347(1), pages 717-741, April.
    • Handle: RePEc:spr:annopr:v:347:y:2025:i:1:d:10.1007_s10479-023-05506-z
    DOI: 10.1007/s10479-023-05506-z
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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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