ESG news sentiment and stock price reactions: A comprehensive investigation via BERT

In this paper, we examine in a systematic manner how investors react to the sentiment of instant ESG news. Instead of acquiring proprietary ESG news or events datasets directly from specific ESG data providers, we extract fresh ESG news directly from a plethora of raw news articles. We showcase how...

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Bibliographic Details
Published in:Schmalenbach Journal of Business Research 2024-06, Vol.76 (2), p.197-244
Main Authors: Dorfleitner, Gregor, Zhang, Rongxin
Format: Article
Language:English
Subjects:
Accounting/Auditing
BERT
Business and Management
Datasets
ESG
Finance
Instant ESG News
Investments
Investor behavior
Investors
Management
Marketing
Media coverage
NLP
Original Article
Production
Proprietary
Securities markets
Sentiment Analysis
Social investing
Stock prices
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Summary:In this paper, we examine in a systematic manner how investors react to the sentiment of instant ESG news. Instead of acquiring proprietary ESG news or events datasets directly from specific ESG data providers, we extract fresh ESG news directly from a plethora of raw news articles. We showcase how the latest development in NLP (i.e. the BERT model) can be applied to build a comprehensive and fresh ESG news dataset, and how company ESG news sentiment can be efficiently recognized by a machine. Overall, we find that the market reacts to ESG news based on news sentiment. On the event day, positive ESG news has an average abnormal return of 0.31% while negative ESG news leads to a mean value of -0.75%. More interestingly, we find that the impact of ESG news may depend on the company's historical ESG record. The negative impact of negative ESG news has less severe consequences for companies with an overall better ESG record, while the positive impact of positive ESG news may be more pronounced for companies with a worse ESG record.
ISSN:2366-6153
2366-6153
DOI:10.1007/s41471-024-00185-3