Based on institutions' general role and the specialty of motivated investors' relatively larger stake, we examine whether ownership by motivated investors is associated with the focal firm's ESG rating disagreement in China. Our results suggest that ownership by motivated investors can decrease the focal firm's ESG rating disagreement. That relationship is strengthened by a better internal or external information environment. What's more, ownership by motivated investors can increase the quality of ESG disclosure and the level of consensus ESG rating. ESG rating disagreement increases stock return volatility and price synchronicity, while motivated investors can mitigate those negative effects. Our results confirm that motivated investors have greater incentive and capability to discipline managers and influence corporate policies and actions even in an emerging market with weak investor protection and the popularity of exploration by ultimate controllers. That would shed valuable insights into the high-quality development of other emerging markets, especially those in south-east Asian.

We propose a novel measure, DOT, to capture belief divergence on extreme tail events in stock returns. Defined as the standard deviation of expected probability forecasts generated by distinct information processing functions and neural network models, DOT exhibits significant predictive power for future stock returns. A value-weighted (equal-weighted) long-short portfolio based on DOT yields an average return of -1.07% (-0.98%) per month. Furthermore, we document novel evidence supporting a risk-sharing channel underlying the negative relation between DOT and the equity premium following extreme negative shocks. Finally, our findings are also in line with a mispricing channel in normal periods.

This paper investigates the high-frequency dynamics of macroeconomic expectations and disagreement among professional forecasters. We propose a novel mixed-frequency estimation approach that integrates daily asset returns with quarterly expectation data from the Survey of Professional Forecasters. Our findings indicate that consensus forecasts are updated efficiently according to Bayes' rule, independent of prior forecasts. By employing "representative forecasters" as proxies for real-world agents, we derive a simple yet intuitive evolution equation for disagreement, revealing that changes in disagreement are primarily driven by different interpretations of new information. Furthermore, we reconstruct daily series of expectations and disagreement concerning macroeconomic growth, achieving impressive R2 values of 93.3% and 84.5% against the true quarterly series.

Using the data of Chinese listed firms from 2003-2020, this study applies a System GMM estimation approach to document that high local government ecological concerns increase a firm’s stock price crash risk. This finding remains consistent after addressing endogeneity issues and undergoing robustness checks. This study also reveals that the implementation of the new environmental protection law in 2015 mitigates the relationship between local government ecological concerns and stock price crash risk. Further analyses indicate that stricter environmental regulation and high subsidies, as well as enhanced corporate social responsibility and governance, can effectively alleviate the adverse effect of local government ecological concerns on stock price crash risk. In addition, we note that the influence of local government ecological concerns on stock price crash risk is more significant in the eastern region, heavily polluting industries, and non-SOEs. Lastly, the research identifies two potential channels through which local government ecological concerns can impact stock price crash risk by reducing the quality of information disclosure and intensifying investor disagreement.

We investigate the causal impact of a company's environmental and social (ES) risk on the borrowing costs of its peer firms (that share lending banks). Using a regression discontinuity design based on the voting outcomes of ES-related shareholder proposals in US public companies' annual meetings from 2005 to 2021, we find that the passage of ES-related proposals leads to an average increase of 38 basis points in the loan costs for peer firms in the subsequent year. The negative spillover is more pronounced for peers with lower bargaining power in their banking relations or having lower ex-ante ES scores, on credit lines rather than term loans, and during the earlier years, validating that banks indeed channel the spillover. Notably, the spillover is particularly significant if the peer firms locate in the same states as the focal firm, or when the proposals reflect a higher degree of disagreement between the proposing shareholders and the managers, or for loans issued by banks lacking prior incentives or expertise in pricing ES risks (``non-ES banks''). We interpret these findings as evidence that the passage of ES-related shareholder proposals releases new information related to peers' ES risks and especially raises the awareness of ES risks among non-ES banks, prompting them to adjust loan rates for their portfolio companies accordingly.

This study explores how Chinese mutual fund managers’ degrees of disagreement (DOD) on stock market returns affect investor capital allocation decisions using a novel textbased measure of expectations in fund disclosures. In the time series, the DOD negatively predicts market returns. Cross-sectional results show that investors correctly perceive the DOD as an overpricing signal and discount fund performance accordingly. Flow-performance sensitivity (FPS) is diminished during high dispersion periods. The effect is stronger for outperforming funds and funds with substantial investments in bubble and high-beta stocks, but weaker for skilled funds. We also discuss ffnancial sophistication of investors and provide evidence that our results are not contingent upon such sophistication.

Using data from Chinese A-share listed companies from 2010 to 2021, we examined the impact of ESG rating disagreement on stock price synchronicity and its mechanisms. We discovered that ESG rating disagreement increases stock price synchronicity by raising investors' information costs and reducing the efficiency of ESG information incorporation into prices. This effect is more pronounced when average ESG ratings are either low or high. Our findings highlight how ESG rating disagreement affects stock price synchronicity and provide insights for regulators to standardize rating criteria and foster a conducive ESG investment environment, promoting pricing efficiency in the capital markets.

This paper explores the relationship between ESG rating disagreement and the stock price crash risk. Using 2011-2020 Chinese A-share listed companies in Shanghai and Shenzhen as research sample, the empirical test results show that ESG rating disagreement significantly increases the stock price crash risk. The mechanism tests find that ESG rating disagreement influences the stock price crash risk by undermining corporate information transparency and increasing the level of investor sentiment. The findings of this paper reveal the potential negative economic consequences of ESG rating disagreement and enrich the research on the influencing factors of stock price crash risk, which contribute to the prevention of possible financial risk and the sustainable development.

It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor’s attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little we really know about trading volume. Here we show that trading volume probability represents the frequency of market crowd’s trading action in terms of behavior analysis, and test two adaptive hypotheses relevant to the volume uncertainty associated with price in China stock market. The empirical work reveals that market crowd trade a stock in efficient adaptation except for simple heuristics, gradually tend to achieve agreement on an outcome or an asset price widely on a trading day, and generate such a stationary equilibrium price very often in interaction and competition among themselves no matter whether it is highly overestimated or underestimated. This suggests that asset prices include not only a fundamental value but also private information, speculative, sentiment, attention, gamble, and entertainment values etc. Moreover, market crowd adapt to gain and loss by trading volume increase or decrease significantly in interaction with environment in any two consecutive trading days. Our results demonstrate how interaction between information and news, the trading action, and return outcomes in the three-term feedback loop produces excessive trading volume which includes various internal and external causes. Finally, we reconcile market dynamics and crowd’s trading behaviors in a unified framework by Shi’s price-volume differential equation in stock market where, we assume, investors derive a liquidity utility expressed in terms of trading wealth which is equal to the sum of a probability weighting utility and a reversal utility in reference to an outcome. JEL Classifications: G12, G02, D83 （长期以来，金融学术领域里的文献只注重价格和收益率，却较少研究交易量。在最近的二十年里，金融学术文献已经开始研究价格和交易量两者与经济基本量之间的相互关系，并且探讨交易量的行为内涵，例如投资者对风险的态度、过度自信、不同观点以及关注程度等等。然而，我们还是对交易量的认识知之甚少。本文根据行为分析，用交易量概率来表示市场群体的交易频率，并且通过我国股市来实证检验涉及交易量与价格之间不确定关系的两种适应性假说。实证结果表明：市场群体在每日交易的时间窗口内除了采用简单的经验法则之外，同时还采用有效的适应性方式来从事股票交易，并且逐步倾向于形成一个结果和认同的资产价格；无论该资产价格是否明显地被高估或低估，市场群体在相互作用和竞争的过程中往往能够形成这样一个稳态的均衡价格。这表明了资产价格不仅包含了基本价值同时还包含了非公开信息、投机、情绪、关注、赌博和娱乐等价值。此外，在任意两个连续交易日之间，市场群体在与市场环境的相互作用过程中，通过交易量的增加或减少来有效地适应盈亏。我们的研究结果说明了在由信息、交易与收益结果三项构成的反馈环中，它们之间的相互作用是如何导致了过度交易的，这其中包含了导致过度交易的各种内外因素。最后，我们假设股票市场中的投资者是通过交易财富来产生流动性效用，它等于概率加权效用与相对于结果为参照系的反转效用之和，从而推导出Shi氏价-量微分方程，将市场动力学行为与群体交易行为协调在一个统一的框架体系。）

It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor’s attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little we really know about trading volume. Here we show that trading volume probability represents the frequency of market crowd’s trading action in terms of behavior analysis, and test two crowd’s trading behavioral hypotheses relevant to the volume uncertainty associated with price in China stock market. The empirical work reveals that market crowd trade in simple heuristics and efficient adaptation, gradually tend to achieve agreement on an outcome or an asset price widely on a trading day, and generate such a stationary equilibrium price very often in interaction among themselves no matter whether it is highly overestimated or underestimated, suggesting that asset prices include not only a fundamental value but also private information, speculative, sentiment, gamble, and entertainment values etc. In addition, market crowd adapt to gain and loss by trading volume increase or decrease significantly in interaction with environment in any two consecutive trading days. Our results demonstrate how interaction between information and news, the trading action, and return outcomes in the three-term feedback loop produces excessive trading volume which includes various internal and external causes. Finally, we reconcile market dynamics and crowd’s trading behaviors in a unified framework by Shi’s price-volume differential equation in stock market where, we assume, investors derive a liquidity utility expressed in terms of trading wealth which is equal to the sum of a probability weighting utility and a reversal utility in reference to an outcome. JEL Classifications: G12, G02, D83 (长期以来，金融学术领域里的文献只注重价格和收益率，却较少研究交易量。在最近的二十年里，金融学术文献已经开始研究价格和交易量两者与经济基本量之间的相互关系，并且探讨交易量的行为内涵，例如投资者对风险的态度、过度自信、不同观点以及关注程度等等。然而，我们还是对交易量的认识知之甚少。本文根据行为分析，用交易量概率来表示市场群体的交易频率，并且通过我国股市来实证检验交易量与价格之间不确定关系中关于群体交易行为的两个基本假说。实证结果表明：市场群体在每日交易的时间窗口内采用简单的经验法则和有效的适应方式来从事交易，并且总是逐步地倾向于形成一个结果和认同的资产价格；无论该资产价格是否明显地被高估或低估，市场群体在相互作用的过程中往往能够形成这样一个稳态的均衡价格，这表明了资产价格不仅包含基本价值同时还包含非公开信息、投机、情绪、赌博和娱乐等价值。此外，在任意两个连续交易日之间，市场群体在与市场环境的相互作用过程中，通过交易量的增加或减少来有效地适应盈亏。我们的研究结果说明了在由信息、交易与收益结果三项构成的反馈环中，它们之间的相互作用是如何导致了过度交易的，这其中包含了导致过度交易的各种内外因素。最后，我们假设股票市场中的投资者是通过交易财富来产生流动性效用，它等于概率加权效用与相对于结果为参照系的反转效用之和，从而推导出Shi氏价-量微分方程，将市场动力学行为与群体交易行为协调在一个统一的框架体系。)