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New Alpha from ESG2.0™ Factors – U.S. Large Cap - 10-Year Study

alternative-data
quantitative
machine-learning
factset
truvalue
esg

(Eliot Caroom) #1

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New research incorporates an unprecedented 11-year historical dataset on the full investable universe of U.S. stocks. The study shows that alpha-generating “signals” derived from Truvalue Labs’ ESG data significantly outperform the Russell 1000 ® index over time.

The study, “New Alpha from ESG 2.0 ™ Factors”, examines the impact that TruValue Labs’ data has on investment strategies and confirms that the company’s ESG factors enable significant annual outperformance vs. the Russell 1000® index for over a 10-year period. TruValue Labs’ ESG methodology incorporates both positive and negative company actions calculated on a daily basis and thereby provides investors with more timely, actionable information in their investment decisions.

Learn about the backtest results on the effectiveness of timely Environmental, Social, and Governance (ESG) signals as screening tools and quantitative “alpha” factors for large-cap U.S. stocks. Truvalue Labs’ timely signals scored by artificial intelligence constitute a new tool for the investment industry.

This study was conducted by Dr. Stephen Malinak, Chief Data and Analytics Officer for Truvalue Labs. Malinak leads Truvalue Labs’ quantitative research team in applying artificial intelligence and machine learning techniques to create new financial signals from unstructured data. An industry leader in quantitative analytics, Stephen joined Truvalue Labs from Thomson Reuters, where he spearheaded the company’s quantitative analytics offering, StarMine, and developed more than 15 quantitative models.

Readers can download the full study white paper using this link.