Examination of the Enhanced Fama-French Three-factor Model Approach Based on ESG Individual Data

The purpose of this study is to find out if the Fama-French three-factor model’s explanatory power can be increased by include Environmental, Social, and Governance (ESG) elements. The study advances the theoretical foundation of asset pricing models, which benefits academia. From 2018 to 2023, Fama-French three-factor data, stock returns, and annual ESG scores for five businesses listed on the Chinese A-share market were gathered using quantitative analytical techniques. Regression analyses were conducted to construct models both including and excluding ESG factors for comparative purposes. The results indicate that the inclusion of ESG scores increased the model’s R-squared from 30.02% to 32.15%, suggesting that ESG factors significantly enhance the model’s ability to explain stock returns. In the individual analysis of BYD, the R-squared notably increased to 75.64%. The results show that ESG scores are important in explaining stock returns, even if the corrected R-squared was negative because of the small sample size. In summary, the incorporation of ESG factors effectively captures return variations that the traditional three-factor model fails to explain, thereby optimizing the overall explanatory power of the asset pricing model. This finding not only provides investors with a more comprehensive basis for decision-making but also offers empirical support for corporate management and regulatory bodies to promote improvements in ESG performance, thereby facilitating the sustainable development of enterprises and enhancing market recognition.