Mispricing of Climate Risk

Abstract: Purpose: Study the relationship between stock returns and GHG emissions regarding a risk premium related to greenness. This by using GHG emissions estimated by Bloomberg rather than companies self-reported estimates. Methodology: The study conducts a time-invariant model by cross-sectional OLS regression to estimate the risk premium for greenness. Weighted Least Square regression (WLS) to estimate the cross-sectional estimator, which captures market imperfections. A factor capturing greenness is constructed and tested together with three factor models: Capital Asset Pricing Model (CAPM), Fama-French 3 Factor Model and Carhart 4 Factor Model. Theoretical perspectives: The leading theoretical theory is the efficient market hypothesis and the risk premium combined with investors' taste and demand for green investments. Empirical foundation: Daily stock returns of 1602 European companies with mega, large, mid, and small market capitalization, excluding the financial institution and real estate sector for the period March 2021 to February 2022 (12 months). Conclusions: A positive risk premium is found for green companies regarding its main model. The authors conclude that due to sudden higher demand for green stocks through abrupt market shocks, the equilibrium is in transition and therefore does not show a negative premium that would price climate risk accordingly.