Scientific Beta

Traditional ESG scores/ratings attempt to translate measures or assessments of performance across a host of criteria into one convenient number representative of overall corporate performance. Whereas exclusionary screening, which remains the most widely applied ESG strategy globally, does not rely on ESG scores, other popular strategies often make use of these data. While this serves the commercial interests of rating providers, academic research has underlined that these scores could not guide issuers or investors concerned with social welfare and environmental sustainability. Scientific Beta therefore eschews weighting index constituents on the basis of ESG scores, which would magnify the estimation errors associated with them, and refrains altogether from using these scores for its off-the-shelf ESG and Climate options.

Traditional scores/ratings for a company’s Environmental, Social and Governance (ESG) credentials attempt to translate assessments across a host of criteria into one convenient number representative of overall corporate performance. They have been advertised to investors as relevant metrics that support comparisons across companies as well as computation of aggregate portfolio performance indicators for purposes of reporting and fund selection.

Whereas exclusionary screening, which remains the most widely applied ESG strategy globally, does not rely on ESG scores, other popular strategies often do. This is notably the case for:

• best-in-class strategies that retain as constituents those companies achieving the best ESG scores within their sector;
• composite strategies that determine constituent weight by mixing issuer-level ESG data with financial inputs; and;
• optimisation-based strategies that weight constituents to achieve ESG and financial constraints or objectives – in particular linked to average ESG scores – simultaneously at the level of the portfolio.

While this serves the commercial interests of rating providers, academic research has underlined that these scores could not guide investors concerned with social welfare and environmental sustainability. International organisations as diverse as the OECD and the WWF have warned against viewing ESG scores as a meaningful indicator of an investment strategy’s contribution to the achievement of ESG goals, in particular the fight against climate change.

These dire warnings are buttressed by the amply documented lack of convergence of ESG scores across the different providers. This divergence, which we analyse in the first section of this paper, is due not only to differing objectives, definitions, methodologies and data, but also to the inherent subjectivity of assessment.

In the second part, we highlight the additional concerns linked to averaging ESG scores across a portfolio and using such an average as a goal or constraint in the portfolio construction. Portfolio optimisations based on average ESG scores magnify the estimations errors of individual ESG scores. Moreover, average ESG scores can only be viewed as relevant if one makes questionable assumptions on investors’ utility functions with respect to ESG performances and/or unrealistic assumptions about the link between ESG scores and the ESG risks of companies.

The lack of convergence of ESG scores is nevertheless not an indictment of all ESG data. Indeed, the ESG screens incorporated in Scientific Beta’s off-the-shelf ESG and Climate options do not seek to manage an average score at the level of the index but impose the same minimum ESG standards on all constituents. Thus, concerns about portfolio-level financial or ESG performances are not permitted to distract from the removal of securities of issuers whose activities or behaviours violate global ESG norms – violations that can documented with reasonable objectivity. Scientific Beta prefers involvement indicators shedding lights on inconvenient truths to the convenience of portfolio averages which may obscure issues.

To address the most important and pressing ESG issue facing investors, i.e. the fight against climate change, Scientific Beta indices can combine such norms-based divestment with filtering or weighting on the basis of greenhouse gas emissions data of sufficient specificity. Focusing on emissions data with reasonable convergence is a more sensible way to tackle climate change than relying on divergent environmental scores, which an OECD study recently described as ineffective tools to assess the environmental impact of companies and counter-productive indicators from the point of view of climate change mitigation.