Natural Language Processing for Automated ESG Portfolio Construction

Explore the intersection of Natural Language Processing (NLP) and Environmental, Social, and Governance (ESG) investing in this 38-minute conference talk by Kyle Caverly, Machine Learning Researcher at RiskLab Toronto. Discover how investment firms can leverage NLP tools to automatically adjust portfolio construction methods in response to ESG considerations. Learn about the importance of incorporating dynamic ESG metrics into investment processes and how publicly available news sources can be used to generate ESG-adjusted portfolios. Delve into recent research from RiskLab Toronto, focusing on weak supervision and Black-Litterman methods for automated ESG portfolio construction. Gain insights into the application of Transformer-based classification algorithms trained under weak supervision and their integration into the Black-Litterman Portfolio Optimization process. Understand how these advanced machine learning techniques can help financial firms align their investments with public expectations surrounding environmental, social, and ethical implications.

Natural Language Processing for Automated ESG Portfolio Cons