Empirical research on ESG factor optimized asset pricing and multifactor models
Sinian Zheng  1, *@  , Valerio Poti  1, *@  , Alessia Paccagnini  1, *@  
1 : University College Dublin
* : Corresponding author

In the realm of asset pricing models, traditional methods primarily focus on financial metrics to explain stock returns, often overlooking non-financial factors. Particularly in emerging markets like China, the integration of Environmental, Social, and Governance (ESG) factors remains underexplored, despite their growing relevance in global investment strategies. This gap highlights a critical need to understand how ESG factors, when incorporated into asset pricing models, affect stock returns across different sectors and firm sizes. This study advances the field by extending the classic Fama-French three-factor model to include an ESG factor, forming a four-factor model tailored to the Chinese stock market. By constructing size-value and size-ESG investment portfolios, we systematically explore the model's explanatory power. Empirical analysis of these portfolios across various firm sizes and industry sectors demonstrates that including ESG factors not only enhances the model's ability to account for cross-sectional stock returns but also reveals significant sector-specific effects, particularly in industries where ESG considerations are most material. The findings confirm that ESG integration into asset pricing models provides a more nuanced understanding of risk and return, reflecting the complex interplay between traditional financial metrics and ESG factors in China's dynamic capital markets. By aligning investment strategies with sustainable development goals, this approach not only benefits investors but also supports broader economic sustainability initiatives in emerging economies. The enhanced model promises to guide future research and practice in sustainable finance, advocating for a comprehensive view of asset valuation that includes ESG factors as a standard component.


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