This paper utilizes data from Chinese A-share listed companies and, based on the limited attention theory, reexamines the impact of data asset disclosure on capital market pricing efficiency. The study finds that the economic consequences of data asset disclosure are not static but exhibit a significant marginal decreasing feature as the overall market disclosure level rises. Specifically, when the overall market disclosure level is low, corporate disclosure of data asset information can significantly reduce stock price synchronization and enhance capital market pricing efficiency by increasing the supply of idiosyncratic information, enhancing information diffusion, and accelerating information integration. However, with the recent widespread disclosure behavior, there is no evidence that the above mechanisms remain effective. Further analysis indicates that disclosure behavior can maintain its positive effect only when the overall market disclosure level of data assets is low, and the firm's disclosed idiosyncratic information is relatively limited, the information dissemination environment is favorable, or institutional investor attention is not excessively diffused. This paper expands the boundaries of the limited attention theory, extending the research perspective to the dimension of the dispersion of investor attention by homogenized information, and reveals the value dilution problem faced by data asset information disclosure in the context of universalization.

Purpose-This study explores how inconsistency in environmental, social and governance (ESG) ratings affects the information environment of publicly traded companies in emerging markets. Design/methodology/approach-Drawing on data from six ESG rating agencies covering listed Chinese firms from 2010 to 2022, we construct measures of pairwise ESG rating divergence and average them across 15 unique rater pairs. We then employ a battery of econometric methods to examine how inconsistencies in ESG ratings affect stock return synchronicity in the Chinese capital market. Findings-Our findings indicate that greater ESG rating divergence correlates with increased stock return synchronicity, suggesting a decline in the dissemination of firm-specific information. Supporting evidence for this relationship includes reduced private information flow, heightened opportunistic executive sales and decreased stock turnover for firms associated with higher ESG rating divergence. Our analysis suggests that such divergence hinders informed trading by institutional investors and the effect is more pronounced for firms with lower transparency, such as those with fewer analysts, limited investor oversight and sparse ESG disclosure, as well as for firms in non-polluting industries. These findings emphasize that ESG rating divergence exacerbates uncertainty about firms' future performance, discourages informed trading and ultimately restricts the integration of firm-specific information into stock prices. Originality/value-This study adds to the literature on ESG ratings and market efficiency by highlighting the importance of standardizing rating methodologies and improving corporate disclosure to counteract the adverse impacts of rating divergence.

We develop a theoretical model in which investors evaluate dual-listed stocks through the prospect theory value of their historical return distributions. When the prospect theory value (PTV) of A shares exceeds that of H-shares, the A-share price will be higher than the H-share price, generating a persistent equilibrium price premium despite identical fundamentals. Using Chinese A–H dual-listed firms, we find that the PTV difference positively explains the AH premium. A gain–loss decomposition shows that A-shares have higher PTV because their less negative loss contribution more than offsets their smaller gain contribution. Consistent with this result, loss aversion and value-function curvature exhibit stronger pricing relationships than probability weighting. Investor composition shapes the pricing influence of PTV. Our results also explain why the AH premium increased following deeper market integration, like the Shanghai–Hong Kong Stock Connect.

We study how alternative data influences investors’information acquisition and market efficiency from both short-term and long-term perspectives. Using the exogenous introduction of online sales data on a major Chinese financial information platform, we find that such disclosure enhances investors’information processing capacity. In the short term, firms covered by online sales data exhibit weaker market reactions to unexpected earnings, reflecting more accurate earnings expectations. In the long term, online sales disclosure strengthens the link between earnings and stock returns, indicating higher earnings value relevance. These results are robust to a series of endogeneity tests and robustness checks. Cross-sectional analyses indicate that these effects are more pronounced for firms with lower institutional ownership, higher earnings volatility, and greater reliance on online sales. Mechanism analyses show that short-term effects operate through improved analyst forecast accuracy, while long-term effects are jointly driven by higher firms' earnings quality and enhanced analyst performance. These findings offer new perspectives on market efficiency and fresh evidence on investor information processing.

We investigate how investors assess transition risks arising from the discretionary regulatory mandates for nature conservation. We focus on the UN Biodiversity Conference in Kunming, China, a policy shock signaling heightened political commitment to protection. During the conference, firms exhibited negative abnormal stock returns on average. Using a machine learning approach, we identify historical nature-related subsidies to capture firm-level variations in expectations of mandated conservation engagement, beyond measuring corporate environmental (ecological) impacts. This metric negatively correlates with returns during the conference, particularly for firms with high operational volatility, and those in regions with limited fiscal flexibility and stringent conservation pressures. Investor concerns primarily stem from policy uncertainty, without positive earning expectations from conservation. Our findings underscore the role of authoritative discretion in shaping nature transition risks.

This study investigates the role of contextual cues in memory-based decision-making within high-stakes trading environments. Using trade records from a large Chinese brokerage firm, I show that an everyday contextual cue—geographic location—triggers the recall of previously traded stocks: when an investor returns to a city she has visited before, her probability of retrading stocks associated with that city rises by 2.1 percentage points under the most saturated specification (up to 12.2 percentage points under less saturated ones). The effect displays the signatures of similarity-based recall: it is diluted by intervening trading experiences, decays with the age of the memory trace, survives when the city is not the investor's home, is not explained by mechanical recency, and is present for orders submitted via both smartphones and PCs. I then examine an extreme-event cue, COVID-19 quarantine, and find a smaller and less robust effect; the interference and decay signatures are absent precisely for these strongly encoded traces, as the memory account predicts. Memory-cued transactions underperform: stocks bought upon the cue earn about 50 basis points less per week than stocks bought for other reasons on the same day. The study provides causal field evidence for memory-based theories, particularly similarity-based recall, in real-world trading.

The robustness of the securities market is a necessary condition for ensuring the stable operation of the financial market, and stock price fluctuations have always been a major concern for academia and investors. One of the main influencing factors of stock price fluctuations is macroeconomic monetary policy. As one of the important control tools of macroeconomic monetary policy, the impact of benchmark interest rates on stock price fluctuations cannot be ignored. This paper takes Chinese A-shares as the research object, analyzes the impact of benchmark interest rate changes on stock price fluctuations, and further introduces investor sentiment as a mediating variable to analyze its role in the transmission process of monetary policy. This paper selects monthly data of Chinese A-share listed companies from 2018 to 2024 and conducts empirical tests by constructing direct effect models and mediating effect models. The research results show that: First, benchmark interest rates have a significant negative impact on stock price fluctuations; second, benchmark interest rates can indirectly affect stock price fluctuations by influencing investor sentiment, with investor sentiment playing a partial mediating role. The research conclusions of this paper help to deepen the understanding of the transmission mechanism of monetary policy's impact on securities prices, and provide micro-evidence for monetary policymakers to assess the impact of policy adjustments on capital market stability, while also providing a reference for investors to understand the risk characteristics of the securities market under changes in the interest rate environment.

This paper develops a delegation-based framework to explain how institutional design shapes pricing incentives under risk. Using China’s 2016 IPO reform—which abolished prefunding requirements and transferred payment obligations from investors to underwriters—as a natural experiment, we show that introducing subscription-payment risk (SPR) renders underwriter’s partial residual claimants with respect to unpaid allocations. Building on Baron’s (1982) delegation model, we argue that the reform amplifies information asymmetry and induces underwriters to adopt more conservative pricing strategies to manage perceived payment risk. Empirically, IPOs exposed to SPR exhibit greater underpricing and lower offer prices, particularly when investor bids reflect stronger valuation pessimism. The effect tends to be less pronounced for reputable underwriters and when foreign institutional investors participate. Overall, the evidence demonstrates how risk redistribution and institutional frictions jointly shape underwriter behavior and pricing efficiency in primary equity markets.

A central premise of mandatory disclosure regulation is that greater transparency reduces information asymmetry and lowers borrowing costs. We challenge this premise by examining industry-level operational disclosure - a regulatory form that reveals horizontally comparable information across peer firms rather than refining individual firm fundamentals. Exploiting the staggered introduction of mandatory industry-specific disclosure guidelines by Chinese stock exchanges between 2013 and 2019, we find that enhanced industry disclosure significantly widens bond credit spreads by approximately 54 basis points - the opposite of what standard disclosure theory predicts. This counterintuitive effect is more pronounced in non-homogeneous industries, among smaller firms, and for bonds restricted to institutional investors. Mechanism tests confirm two opposing channels: disclosure reduces information asymmetry while simultaneously intensifying product market competition by exposing strategically sensitive operational metrics. Our evidence challenges the one-size-fits-all approach to disclosure regulation and highlights that the competitive implications of disclosed information - not merely its quantity - shape credit risk pricing.

The China Securities Regulatory Commission is allowing firms to use externally financed funds for share repurchases, a recent measure to enable listed companies address valuation pressures and protect investors; however, its implications for corporate marketing decisions remain unclear. Using an event sample of Chinese listed firms that conducted open-market repurchases between 2009 and 2024, this study empirically examines how this market activity financed by different sources influence marketing decisions and explores the underlying mechanisms. The findings show that compared with firms using internal cash for repurchases, those relying on debt financing are inclined to resist myopic marketing decisions, and this negative relationship is pronounced under high analyst coverage and when privately owned listed firms are controlled by family entrepreneurs. These results remain robust after replacing the dependent variables and applying propensity score matching. Overall, this study shows that debt financing to support share repurchases has a long-term beneficial governance impact as it improves earnings quality and protects investor interests, and offers a new perspective on the relationship between financing-based repurchases and marketing myopia, and provides useful policy insights for evaluating the effectiveness of China’s refinancing regulations related to share repurchases, while guiding further refinement.