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Korean Academic Society of Business Administration
[ Article ]
korean management review - Vol. 51, No. 6, pp.1739-1764
ISSN: 1226-1874 (Print)
Print publication date 31 Dec 2022
Received 15 Aug 2022 Accepted 13 Sep 2022
DOI: https://doi.org/10.17287/kmr.2022.51.6.1739

ESG 논란과 주식 수익률: 자연어 처리의 활용

Jeongseok Bang ; Doojin Ryu
(First Author) Department of Economics, Sungkyunkwan University bes5579@skku.edu
(Corresponding Author) Department of Economics, Sungkyunkwan University sharpjin@skku.edu
ESG Controversies and Stock Market Returns: Using a Natural Language Processing


Copyright 2011 THE KOREAN ACADEMIC SOCIETY OF BUSINESS ADMINISTRATION
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This study examines whether corporate value reacts to news and articles disclosing Environmental, Social, and Governance (ESG) controversies by analyzing the daily stock market responses. Based on deep learning techniques, we collect and utilize a large-scale ESG controversy article dataset for the 10-year-long period from 2012 to 2021. By refining the big data and classifying the ESG articles using KoBERT, a natural language processing model, we investigate how the stock market reacts differently depending on the type of ESG controversy issues. We find that stock prices tend to decline in response to the negative news about ESG controversies. We also find that the stock market responds to the news more intensively as the news coverage becomes greater. The financial performance of companies such as operating profit to assets and credit rating affects the extent to which the ESG controversy changes the corporate value in the short term. Under the interdisciplinary framework, our empirical analyses and findings yield insight on how to analyze the news articles containing ESG controversies and broaden our understanding of the influence of ESG controversies on domestic companies.

Keywords:

Deep learning, ESG controversies, Event study, Natural language processing, Stock market response

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∙ The author Jeongseok Bang is currently a master’s candidate in the Department of Economics, at Sungkyunkwan University. He graduated from Sungkyunkwan University (with a dual major in Chemistry and Economics) and currently, is a member of the SKKU BK21 Four program supported by the Ministry of Education. His current research interests are asset pricing, ESG, deep learning, and natural language processing.

∙ The author Doojin Ryu is a full/tenured professor of economics at Sungkyunkwan University. He graduated from Seoul National University (School of Electrical Engineering) and got a Ph.D. degree at KAIST. He was a research fellow at the National Pension Service, an assistant professor at Hankuk University of Foreign Studies, and a full/tenured professor at Chung-Ang University. Prof. Ryu is currently an editor of Investment Analysts Journal (SSCI) and a subject editor of Emerging Markets Review (SSCI), Journal of Multinational Financial Management (SSCI), and Emerging Markets Finance & Trade (SSCI). He is an editorial board member of the Journal of Futures Markets (SSCI) and Asian Business & Management (SSCI).