Portfolio Management with News-Based Sustainability Scores

Ron Große, Viet Hoang Le, Fei Liu and Hans-Jörg von Mettenheim

Chapter 13 in Sustainable Investing:Problems and Solutions, 2024, pp 337-374 from World Scientific Publishing Co. Pte. Ltd.

Abstract: In this chapter, we present a novel approach to produce Environmental, Social, and Governance (ESG) and Sustainable Development Goal (SDG) scores based on near-real-time news. Through the application of Natural Language Processing (NLP) techniques, we extract the relevant entities, topics, and likely effects of the news. The individual information is aggregated into scores on a regular time grid. Based on the scores, we build topic-oriented portfolios and compare them to a benchmark. The data have been provided in the AiData.green database that was co-developed by the authors of this chapter. In our studies, we cover mostly European and US markets. We find that substantial risk-adjusted outperformance of portfolios can be achieved by taking sustainability topics into account.

Keywords: Sustainable Investing; Impact Investing; Corporate Social Responsibility; Materiality; Externalities; Sustainability; ESG; ESG Funds; ESG Factors; ESG Scores; SASB; SDG; DEI; Private Equity; General Partners; Active Ownership; Investment Stewardship; Machine Learning; Natural Language Processing; Large Language Models; Transition Economy; Climate Risk; Net-zero Investing; Divestment; Greenhouse Gas Emissions; Scope 3 Emissions; Modern Portfolio Theory; Venture Investments; Carbon Dioxide Removal; Carbon Credits; Fuel Production; Portfolio Management; Market Sentiment; Factor Investing; Portfolio Optimization; Post-investment Management; Digital Transformation; Fixed Income; Portfolio Performance Measures (search for similar items in EconPapers)
Date: 2024
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