The CAPM in the ESG era: disentangling the general transition risk

Purpose – The purpose of this study, in line with Zerbib’s S-CAPM (2022) and and Hens and Trutwin (2023), is to deploy the theoretical implications of the capital asset pricing model (CAPM) and analyse the impact of environmental, social and governance (ESG) preferences on asset returns within a linear and concise framework, suggesting also a mechanical approach to extrapolate (indirectly) the investors’ view on the evolution of the ESG cycle. Design/methodology/approach – The authors estimate, for each market sub-index (i.e. leader, intermediate and follower), a cross-sectional regression with Huber–White standard errors to account for heteroskedasticity-consistent standard errors. The authors perform an additional analysis to capture the cyclical extent of the phenomenon. Therefore, the authors run also an ordinary least squares rolling (i.e. constantly changing fixed window) regression for analysing changing relationships among variables overtime. The authors conclude estimating the catch-up process prediction through a logit model. Findings – The ESG CAPM model should prove a temporary framework inversely correlated with the maturity of the ESG cycle. The authors show that the phi coefficient (i.e. general transition risk) is not only positive and statistically significant exclusively for the Follower and Intermediate indices, but it is higher for the former. It represents the potential (and likely) extra-return (and risk) arising from the business model “catch-up effect” rather than a mere investor’s preference. So, it is feasible to isolate the “general transition risk” preserving the “systemic risk” to extrapolate information about the investors’ perception on the evolution of the ESG market cycle. Originality/value – The findings contribute to the influential literature that aims to explain the expected extra-performance of passively following an ESG-screened index within the risk–return paradigm, suggesting a linear theoretical integration to the classic CAPM to take into account the ESG premium. The authors empirically test it by creating innovative ESG indices proxies.