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Cited by 425

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

ESG shareholder engagement and downside risk

Open access
Hoepner, Andreas G F, Oikonomou, Ioannis, Sautner, Zacharias, Starks, Laura T, Zhou, Xiao Y·2024·Review of Finance
DOI 10.1093/rof/rfad034
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Abstract

We show that engagement on environmental, social, and governance issues can benefit shareholders by reducing firms’ downside risks. We find that the risk reductions (measured using value at risk [VaR] and lower partial moments) vary across engagement types and success rates. Engagement is most effective in lowering downside risk when addressing environmental topics (primarily climate change). Further, targets with large downside risk reductions exhibit a decrease in environmental incidents after the engagement. We estimate that the VaR of engagement targets decreases by 9 percent of the standard deviation after successful engagements, relative to control firms.

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Crossref · 10.1093/rof/rfad034

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Metadata

Authors
Hoepner, A. G. F., Oikonomou, I., Sautner, Z., Starks, L. T., & Zhou, X. Y.
Venue
Review of Finance
Publisher
Oxford University Press (OUP)
Published
2023-10-03
Volume
28
Issue
2
Pages
483-510
ISSN
  • 1382-6662 (ISSN-L)
  • 1572-3097
  • 1573-692X
DOI
10.1093/rof/rfad034
OpenAlex
W4387342020
Cited by
425
References
37
FWCI
79.17
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: ESG shareholder engagement and downside risk. https://app.cochat.ai/papers/10.1093/rof/rfad034
The paper
Hoepner, A. G. F., Oikonomou, I., Sautner, Z., Starks, L. T., & Zhou, X. Y. (2024). ESG shareholder engagement and downside risk. Review of Finance. https://doi.org/10.1093/rof/rfad034

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.