ESG: From Heterogeneity to Risk Factor

  Part III: The complementarity of sentiment data 

Published on July 11th, 2022Market and research
Winter in... Coming?
Flageollet

Alexis Flageollet, PhD

Financial Engineer

Juan-Sebastian Caicedo,

Juan Sebastian Caicedo, CFA

Equity Portfolio Manager

Written in March 2022

      

In the first two parts of this paper, we discussed the degree of heterogeneity that exists between the scores of different ESG rating providers and, in a second step, the importance of combining these different sources to improve the estimation of an ESG market factor.

 

Find part 1 on data heterogeneity here.

Find part 2 on the existence of an ESG risk factor here.

  

In this third and last part, we want to explore what benefits, both conceptual and practical, may result from the use of alternative data in addition to existing fundamental data. More concretely, nascent data based on sentiment analysis, estimated from recent artificial intelligence techniques, seem to be particularly interesting thanks to their complementary characteristics. This approach is part of the same informational complementarity objective that we have discussed so far and shows how the concept of “universal” ESG involves the measurement and analysis of different more directly observable variables.

    

Access the Equity Insights - The complementarity of sentiment data

This article has been provided for information purposes only to professional clients as defined in the MiFID Directive. It must not be used for retail investors. The provision of this material or reference to specific sectors or markets in his article does not constitute investment advice or a recommendation or an offer to buy or sell any security. Investors should consider the investment objectives, risks, and expenses of any investment carefully before investing. Views expressed in this article as of the date indicated are subject to change and there can be no assurance that developments will transpire as may be forecasted in this article.