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| Valuation Correction or Information Confusion？— A Study on ESG Ratings from Multiple Agencies and Stock Mispricing |
| ZHANG Weiwei, ZHANG Jingjing, CHEN Pan, ZHANG Detao
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| Northeast Asia Research Center, Jilin University;School of Economics, Shandong University |
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Abstract The fundamental function of capital markets is to guide resource allocation through security price signals, which must accurately reflect fundamental value (also known as intrinsic value) to be effective. Stock mispricing, which means that prices deviate from their fundamental value, impairs this function. Thus, studying the drivers and mechanisms of stock mispricing is crucial for restoring fair valuation and advancing capital market quality. With growing awareness of sustainable development, ESG (Environmental, Social, and Governance) has become a key factor in investment decisions. Rating agencies, as professional processors, release ESG ratings that investors use to assess company risks. However, ESG ratings often diverge across agencies for the same company. Understanding how these divergences affect stock prices' reflection of intrinsic value is vital for capital market effectiveness in supporting the real economy.
This paper constructs a theoretical model to analyze how ESG rating divergence drives heterogeneous beliefs to impact stock mispricing. It examines the roles of information transparency and noise traders, and investigates whether ESG rating divergence leads to stock overvaluation or undervaluation, especially under short-selling constraints, and further investigate the heterogenous impact of ESG rating divergence on mispricing. Based on the Atmaz and Basak (2018) model, the study builds a theoretical model of how ESG rating divergence affects stock price deviations from intrinsic value and further discusses the mispricing effect and the mechanism embedded. Empirically, it tests these effects using a sample of non-financial firms listed on the Shanghai and Shenzhen A-share markets, rated by 10 agencies from 2010 to 2022, and evaluates the impact, mechanisms and conditional heterogeneity of the findings.
The research findings are as follows: The theoretical model confirms that ESG rating divergence exacerbates stock mispricing over time, with its impact increasing as the divergence increases. Empirically, ESG rating divergence worsens stock mispricing by reducing information transparency, increasing heterogeneous beliefs and affecting noise traders. Specifically, the “information confusion effect” caused by divergent ESG ratings drives stock prices further away from their intrinsic values. Impact Direction: Under short-selling constraints, ESG rating divergence primarily leads to stock overvaluation, indicating that significant divergence tends to overprice stocks. Impact Heterogeneity: When regulatory bodies mandate ESG disclosure, divergent ratings assist investors in assessing corporate ESG performance, playing a “valuation correction” role. However, the internal characteristics of voluntarily disclosed ESG information do not significantly influence the mispricing impact. Comprehensive ESG disclosures and investor interpretation abilities reduce the impact of rating divergence on mispricing. For firms with high-quality financial information, the marginal “information confusion” effect is stronger, resulting in more pronounced mispricing. These results enhance the understanding of ESG rating divergence and its implications for capital markets, offering insights for aligning stock prices with intrinsic values and improving stock market resource allocation.
The contributions and innovations of this paper are as follows: (1) From the perspective of stock price deviations from intrinsic value, this study extends Atmaz and Basak's (2018) heterogeneous belief model to the context of stock mispricing by innovatively introducing the ESG rating divergence factor. This study introduces stochastic differential equations to describe investors' heterogeneous beliefs and a stochastic system with ESG rating divergence is established. Based on the Kalman filter theory, the paper derives the intrinsic mechanism of ESG rating divergence affecting mispricing. The research findings theoretically model how divergent ESG ratings released by multiple rating agencies influence mispricing by driving heterogeneous beliefs. This provides a theoretical basis for regulating the rating market and improving the information environment in capital markets, while also offering a reference model framework for future studies on information disparities in financial markets. (2) The study validates the mispricing effect of ESG rating divergence and finds that ESG rating divergence primarily leads to stock overvaluation. While previous literature has explored ESG rating divergence's relationship with market metrics like stock price and return synchronicity, it has not addressed its impact on the accurate reflection of intrinsic value. This study clarifies the mispricing effects, highlighting market inefficiencies and offering evidence to identify pricing gaps and prevent market bubbles. (3) The study introduces internal and external ESG disclosure characteristics, showing that divergent ESG ratings can correct valuations under certain conditions through the “information production effect”. It also examines how ESG information recognition and financial information quality interact with ESG rating divergence, expanding the understanding of ESG ratings' role and their influence on market behavior.
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Received: 09 July 2023
Published: 02 December 2024
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