A Sustainable Extension of the Fama-French Factor Models: The Role of Carbon Emissions-Based Factors in Describing U.S. Stock Returns

Abstract

Amidst climate change concerns, many investors are incorporating climate-related considerations, such as a company's carbon dioxide (CO2) emissions, into their investment decisions. Unfortunately, CO2 data is often missing or estimated. Therefore, we aim to understand how companies' carbon emissions can describe --- and how sector membership and carbon disclosure can impact --- excess stock returns. We extend the Fama-French (FF) three-factor and five-factor models, which describe stock returns using financial metrics, to also include our constructed ``Green-Minus-Brown" (GMB) factors: GMB_U (based on Log(CO2) emissions), and GMB_S (based on CO2 intensity). Our results show (1) Both GMB_U and GMB_S are statistically significant and have negative associations with excess stock returns; (2) Stocks in greener sectors have more positive interactions with the GMB factors, stocks in browner sectors have more negative interactions, and sectors with less polarizing CO2 emissions tend to have statistically insignificant interactions; and (3) The returns of companies with reported CO2 data are more sensitive to changes in the GMB factors than those with estimated CO2 data. Our research supports existing literature that carbon emissions can be used to describe stock returns while being the first to build factors based on both unscaled and scaled carbon emissions and to analyze performance across sectors and CO2 data sources (i.e., estimated vs. reported). In addition, our GMB factors can be used by companies and investors alike to track the monthly spreads between the excess returns of green stocks and the excess returns of brown stocks.