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Objectivity
It is well known that there is a relatively low correlation across the major data vendors’ ESG ratings highlighting subjectivity and measurement error. A systematic approach based upon empirical evidence overcomes these concerns.
Investors typically misprice the financially material aspects of sustainability. This behaviour provides a source of potential alpha.
It is well known that there is a relatively low correlation across the major data vendors’ ESG ratings highlighting subjectivity and measurement error. A systematic approach based upon empirical evidence overcomes these concerns.
Our investment team includes experts in machine learning, data science techniques, and alternative data to create forward-looking material ESG signals. We do not use ‘off-the-shelf’ scores within our investment process.
We pay careful attention to the formulation of ESG signals across sectors, regions, and time based upon their efficacy.
A key strength of our process is the ability to weigh the relative importance of ESG metrics alongside company fundamentals.
Proprietary and data-driven ESG signals built from unstructured data and machine learning to enhance the prediction of risk-adjusted returns
Ability to integrate sustainability preferences (exclusions, tilts, decarbonisation) typically with negligible or measured impact on alpha exposure
Engagements playing to the strength of data analysis and sophisticated quantitative insights
Many of our clients ask us to further integrate their values-based sustainability views into portfolios. Consequently, much of our work involves partnering with clients to meet their specific needs. If an ESG consideration is deemed to be a source of alpha, it’s already integrated into our investment process. For clients’ values-based views that go beyond the level of ESG integration within our alpha model, we evaluate the trade-off between ESG exposure vs. alpha exposure.
Aside from regulatory or specific client requirements, our commitment to ESG innovation is for the principal purpose of enhancing risk-adjusted returns. This is underpinned by our proprietary empirical research which finds that investors typically underreact to a range of non-financial information. In our view, a systematic process is the most effective way to analyse ESG return drivers and implement them successfully in portfolios. Systematic investing’s central features—its use of alternative data, structured forecasting methods, and flexible portfolio construction—help us extract alpha from ESG concepts.