A machine learning-based approach to thematic ESG investing: case study in GEO (Green Economy Opportunities) - Acadian Asset Management

Most investors don’t readily associate systematic investing with thematic strategies, yet in the thematic context, the increasingly sophisticated analysis of alternative data can offer substantial benefits.

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Machine learning has surprising benefits in the creation of thematic portfolios. In the climate context, for example, sophisticated natural language processing can identify companies aligned with the energy transition more comprehensively using richer information and in a more timely fashion, than traditional methods. By exploiting the resulting investment universe, a systematic investing approach can produce thematic portfolios that have superior financial characteristics relative to conventional, narrow thematic strategies.

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