Abstract
We provide a new methodology for ESG factor construction. We analytically compare two dominant methodologies, the time-series (ESG ratings used as ordinal variable) and cross-sectional (ESG ratings used as cardinal variable) approaches. When the two factors have identical ratings and other firm characteristics are ignored, their expected returns are equal. This is no longer the case when other characteristics drive expected returns. We construct a cross-sectional factor (i) featuring a targeted rating, (ii) neutralizing exposure to other firm characteristics, being thus a pure ESG factor, and (iii) not harming diversification through stock screening. Using ratings from several ESG data vendors, we document strong variations of the factor alpha in the time series and across data vendors. The conditional alpha filtered from realized returns is negatively related to the level of an ESG sentiment variable based on media attention, while it is positively related to unexpected variations of ESG sentiment.
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