RT Journal Article
SR Electronic
T1 E, S, or G - Analyzing Global ESG Performance
JF The Journal of Impact and ESG Investing
FD PMR
SP jesg.2020.1.003
DO 10.3905/jesg.2020.1.003
A1 Robert Bush
A1 Jason Chen
A1 Eric Legunn
YR 2020
UL https://pm-research.com/content/early/2020/10/03/jesg.2020.1.003.abstract
AB The authors propose a framework for analyzing the risk and return impact of environmental, social, and governance (ESG) investing across regional equity markets. By examining the performance of ESG through passive index exposure via the MSCI ESG Leaders methodology, we seek to determine: 1) whether an ESG investment has generated meaningful, statistically significant alpha in the single-index model, 2) if any such alpha does exist, whether it is simply explained by known risk premia 3) in regions where ESG has empirically added meaningful alpha, which of the three pillars, E, S, or G, has been the main determinant of this alpha, and whether the sensitivity to each of the three pillars has changed over time, and 4) the extent to which any ESG alphas are correlated across regions.TOPICS: ESG investing, portfolio theory, equity portfolio management, behavioral financial, theory, in portfolio managementKey Findings• We propose a framework for analyzing the risk and return impact of environmental, social, and governance (ESG) investing across regional equity markets.• Our framework examines empirical ESG returns via MSCI ESG Leaders methodology to determine 1) statistical significance of alpha, 2) degree of exposure to other known risk premia, 3) sensitivity of alpha to E, S, or G pillars, and 4) interaction of regional ESG alphas for global investors.• We conclude through our three-step framework that 1) statistically significant empirical alpha exists in EM and Canada, 2) size and values factors do not explain much of this empirical alpha, 3) historical sensitivity to pillars is largely weighted toward governance, and 4) finally that regional MSCI ESG Leaders alphas are largely uncorrelated despite utilizing a consistent methodology.