| Título: | ESG narrative analysis and prediction of financial index volatility using text mining and machine learning |
| en : | |
| Autores: | Antonio Carlos Mercer, Autor ; Zacarias Curi Filho, Autor ; Ângela Cristiane Santos Póvoa, Autor |
| Tipo de documento: | documento electrónico |
| Fecha de publicación: | 2025 |
| Dimensiones: | 16 p. / cuadros, gráficos |
| Langues: | Inglés |
| Materias: |
02 - Temático General - UNESCO Análisis de datos ; Discurso ; Información económica ; Inteligencia artificial ; Mercado ; Modelo económico ; Procesamiento de datos ; Responsabilidad social |
| Etiquetas: | Finanzas sostenibles ; Medioambiente, social y de gobernanza (ESG) ; Inteligencia artificial (IA) ; Sustainable finance ; Environmental, Social, and Governance (ESG) ; Artificial intelligence |
| Resumen: | Motivated by the growing significance of Environmental, Social, and Governance (ESG) factors and the market's pronounced sensitivity to real-time information, this study empirically examines the reaction of the New York Stock Exchange (NYSE) to ESG-related news. Leveraging a specialized news corpus, our methodology integrates a Large Language Model (LLM)-driven Natural Language Processing (NLP) pipeline with a classic event study to assess abnormal returns and trading volume. Our findings indicate a pronounced asymmetry in market reaction, whereby the financial penalties associated with negative news substantially exceed the rewards from positive news. Furthermore, we identify a selective and heterogeneous response: the market distinguishes between the distinct impacts of the Environmental, Social, and Governance pillars and focuses its reaction primarily on events of high materiality. Ultimately, this research establishes that the price discovery of ESG information is a dynamic process, conditional on news sentiment, thematic pillar, and the materiality of the reported event |
| Tipo documento SNRD : | documento de conferencia |
| Creative Commons : |
 Esta obra está bajo una licencia Creative Commons Atribución 4.0 Internacional |
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Documentos electrónicos (1)
 ESG narrative analysis and prediction of financial index volatility using text mining and machine learning Adobe Acrobat PDF |
