TY - JOUR
T1 - ESG controversies and investor trading behavior in the Korean market
AU - Bang, Jeongseok
AU - Ryu, Doojin
AU - Yu, Jinyoung
N1 - Funding Information:
This work is supported by IREC, The Institute of Finance and Banking, Seoul National University (The project title is “ESG management, investments, and controversies: based on machine learning and big data”).
Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2023/6
Y1 - 2023/6
N2 - This study examines how investor trading behavior changes following environmental, social, and governance (ESG) controversies by analyzing textual news data. We use deep-learning-based natural language processing to classify news articles into specific categories of controversy. ESG controversies generally increase investors’ trading activities regardless of their type, while their reactions differ by ESG pillar. Interestingly, domestic institutions tend to sell stocks with controversies.
AB - This study examines how investor trading behavior changes following environmental, social, and governance (ESG) controversies by analyzing textual news data. We use deep-learning-based natural language processing to classify news articles into specific categories of controversy. ESG controversies generally increase investors’ trading activities regardless of their type, while their reactions differ by ESG pillar. Interestingly, domestic institutions tend to sell stocks with controversies.
KW - ESG
KW - Institutional investor
KW - Investor trading behavior
KW - Natural language processing
UR - http://www.scopus.com/inward/record.url?scp=85150041149&partnerID=8YFLogxK
U2 - 10.1016/j.frl.2023.103750
DO - 10.1016/j.frl.2023.103750
M3 - Article
AN - SCOPUS:85150041149
SN - 1544-6123
VL - 54
JO - Finance Research Letters
JF - Finance Research Letters
M1 - 103750
ER -