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View Submission - CFE
Title: Alternative data for ESG events monitoring using NLP: Practical quantitative results Authors:  Sylvain Forte - SESAMm (France) [presenting]
Abstract: The purpose is to analyze how negative ESG events (controversies) can be extracted using natural language processing technologies on millions of sources of web data in real time. We test several techniques to create equity long-short strategies that leverage this information to generate alpha.