We examine whether and how mandatory corporate social responsibility (CSR) disclosures affect corporate tax avoidance. Using a CSR disclosure mandate in China that requires a subset of firms to disclose their CSR activities as an exogenous shock to CSR disclosures, our difference-in-differences analyses show that firms affected by the disclosure mandate engage in less tax avoidance relative to control firms. Additional analyses indicate that increased public scrutiny following the disclosure mandate is the likely channel through which mandatory CSR disclosures constrain tax avoidance. Cross-sectional analyses suggest that the effect of the disclosure mandate varies with institutional environments. Overall, our results indicate that the CSR disclosure mandate constrains corporate tax avoidance, which is consistent with mandatory CSR disclosures nudging firms toward more socially desirable behavior.

The healthy operation of the stock market relies on sound liquidity. We utilize the semantic information from disclosure texts of listed companies on the China Science and Technology Innovation Board (STAR Market) to construct a daily corporate network. Through empirical tests and performance analyses of machine learning models, we elucidate the relationship between the similarity of company disclosure text contents and the temporal and spatial correlations of stock liquidity. Our liquidity indicators encompass trading costs, market depth, trading speed, and price impact, recognized across four dimensions. Furthermore, we reveal that the information loss caused by employing Minimum Spanning Tree (MST) topology significantly affects the explanatory power of network topology indicators for stock liquidity, with a more pronounced impact observed at the document level. Subsequently, by establishing a neural network model to predict next-day liquidity indicators, we demonstrate the temporal relationship of stock liquidity. We model a liquidity predicting task and train a daily liquidity prediction model incorporating Graph Convolutional Network (GCN) modules to solve it. Compared to models with the same parameter structure containing only fully connected layers, the GCN prediction model, which leverages company network structure information, exhibits stronger performance and faster convergence. We provide new insights for research on company disclosure and capital market liquidity.

Using unique account-level data from a leading Chinese fintech platform, we investigate how financial influencers, the key information intermediaries in social finance, attract followers through a process of social transmission bias. We document a robust performance-following pattern wherein retail investors overextrapolate influencers’ past returns rather than rational learning in the social network from their past performance. The transmission bias is amplified by two mechanisms: (1) influencers’ active social engagement and (2) their index fund-heavy portfolios. Evidence further reveals influencers’self-enhancing reporting through selective performance disclosure. Crucially, the dynamics ultimately increase risk exposure and impair returns for follower investors.

We construct a novel risk-based similarity peer network by applying machine learning techniques to extract a comprehensive set of disclosed risk factors from firms' annual reports. We find that a firm's future returns can be significantly predicted by the past returns of its risk-similar peers, even after excluding firms within the same industry. A long-short portfolio, formed based on the returns of these risk-similar peers, generates an alpha of 84 basis points per month. This return predictability is particularly pronounced for negative-return stocks and those with limited investor attention, suggesting that the effect is driven by slow information diffusion across firms with similar risk exposures. Our findings highlight that the risk factors disclosed in 10-K filings contain valuable information that is often overlooked by investors.

How much value has been lost in the Chinese bankruptcy system due to excessive liquidation of companies whose going concern value is greater than the liquidation value? I compile new judiciary bankruptcy auction data covering all bankruptcy asset sales from 2017 to 2022 in China. I estimate the valuation of the asset for both the final buyer and creditor through the revealed preference method using an auction model. On average, excessive liquidation results in a 13.5% welfare loss. However, solely considering the liquidation process, an 8% welfare gain is derived from selling the asset without transferring it to the creditors. Firms that are (1) larger in total asset size, (2) have less information disclosure, (3) have less access to the financial market, and (4) possess a higher fraction of intangible assets are more vulnerable to such welfare loss. Overall, this paper suggests that policies promoting bankruptcy reorganization by introducing distressed investors who target larger bankruptcy firms suffering more from information asymmetry will significantly enhance welfare in the Chinese bankruptcy market.

This study explores how Chinese mutual fund managers’ degrees of disagreement (DOD) on stock market returns affect investor capital allocation decisions using a novel text-based measure of expectations in fund disclosures. In the time series, the DOD neg-atively 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 ef-fect 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 sophisti-cation of investors and provide evidence that our results are not contingent upon such sophistication.

The reform of the IPO registration system is a crucial step toward the maturity, improvement, and marketization of the securities market. In recent years, the trend of corporate financialization has become increasingly evident. Based on data from firms listed on the ChiNext Market and the Main Board, this paper constructs a Propensity Score Matching-Difference-in-Differences (PSM-DID) model and an RDD-DID model to examine the impact of IPO registration system reform on corporate financialization and analyze its underlying mechanisms from multiple perspectives. The estimation results of both models indicate that the IPO registration system reform has significantly increased firms’ financialization levels. Furthermore, a series of robustness checks confirm the reliability of the findings. The mechanism analysis reveals that the reform has promoted corporate financialization by lowering listing thresholds, alleviating financing constraints, and intensifying market competition. Meanwhile, its information disclosure mechanism has to some extent curbed financialization. Further heterogeneity analysis shows that the reform’s promoting effect is more pronounced in non-state-owned enterprises, firms with lower growth potential, and those with weaker corporate social responsibility (CSR) performance. This study enriches the literature on the policy impact of IPO registration system reform, provides a new perspective on how such reforms influence corporate financialization, and offers important implications for curbing excessive financialization in real-sector enterprises, deepening IPO registration system reform, and further improving capital markets.

This paper investigates how transparency in lawsuit information affects capital allocation and aggregate industrial production. Greater transparency enhances the availability of information about firms' fundamentals, which can influence resource distribution. We exploit regional variations in courts' compliance with mandated judicial document disclosures in China, implemented since 2014, as a natural experiment. For firms with initially high marginal revenue products of capital (MRPK), a 10-percentage-point increase in legal transparency results in a 4.4% increase in physical capital and a 7.9% reduction in MRPK, relative to firms with lower MRPK. Additionally, regions with higher transparency experience a rise in aggregate output. Further analysis differentiating firms by ownership type, public listing status, and industry-level contract intensity enhances the robustness of our findings.

Site visits allow visitors to physically inspect productive resources and interact with onsite employees and executives face-to-face. We posit that, by allowing visitors to acquire investmentrelated information and monitor the management team, site visits offer disciplinary benefits for corporate investments. Using mandatory disclosures of site visits in China, we find that corporate investments become more responsive to growth opportunities as the intensity of site visits increases, consistent with the notion that site visits yield disciplinary benefits. We also find that the positive association between site visits and investment efficiency is more pronounced when visitors can glean more investment-related information and when they have stronger incentives and greater power to monitor managers. This positive association is also stronger among firms with more severe agency problems and higher asset tangibility. The overall evidence supports the notion that site visits serve as a unique venue for institutional investors and financial analysts to acquire valuable information and serve a monitoring function, which generates disciplinary benefits for corporate investments.

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.