Professor Doojin Ryu co-authored this paper with Jeongseok Bang (Korea Institute of Finance) and Jinyoung Yu (Xi’an Jiaotong-Liverpool University). The research bridges social science (ESG and financial markets) and engineering methods (machine learning, deep learning) to analyze how ESG controversies influence investor behavior using big data.

The study employed deep learning-based natural language processing to systematically analyze news articles, classifying them by specific ESG controversy types. ESG controversies generally increase trading activity, though responses vary by ESG factor. Domestic institutional investors, unlike foreign or individual investors, showed a distinct tendency to sell stocks tied to controversies.

Highlighting the Korean market, it was published in Finance Research Letters, a high-ranking SSCI journal in the Business/Finance category.

Publication Details:

Bang, J., Ryu, D., & Yu, J. (2023). ESG controversies and investor trading behavior in the Korean market. Finance Research Letters, 54 (Jun.), 103750.