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- Title
ESG News Sentiment and Stock Price Reactions: A Comprehensive Investigation via BERT.
- Authors
Dorfleitner, Gregor; Zhang, Rongxin
- Abstract
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.
- Subjects
LANGUAGE models; FINANCIAL market reaction; ABNORMAL returns; MARKET sentiment; SENTIMENT analysis
- Publication
Schmalenbach Journal of Business Research (SBUR), 2024, Vol 76, Issue 2, p197
- ISSN
0341-2687
- Publication type
Article
- DOI
10.1007/s41471-024-00185-3