This paper investigates whether and how independent director-affiliated corporate donations affect stock price crash risk in China. We find a significant positive relationship between affiliated donations and future crash risk. The relationship is more significant for firms with weak internal governance and limited external monitoring, when affiliated directors serve on the audit committee, and in non-state-owned enterprises. Overall, our findings suggest that the social ties built through affiliated donations undermine rather than enhance director monitoring, and that agency theory has more explanatory power than resource dependence theory for understanding the impact of affiliated donations on stock price crash risk.

This article examines the link between foreign institutional holdings and firms’ efficiency in labor investment in the setting of Chinese markets. We find that foreign institutional investors enhance firms’ labor investment outcomes primarily through mitigating asymmetric information and by strengthening internal governance. Specifically, the influence of foreign institutional investors on a firm’s labor investment efficiency is stronger when the firm faces greater labor adjustment frictions. This effect is more evident when foreign institutional investors are originated from countries or areas with stronger cultural connections to China, stronger governance quality, common law traditions, or stronger bargaining power in the firms’ governance. Our paper contributes to the literature in that it documents the monitoring role of foreign institutional investors from the perspective of firms’ labor investment decisions, and adds to the literature on the drivers of firms’ labor investment choices.

Research Question/Issue: This study investigates whether and how political connections affect customer complaints in the Chinese market, using a comprehensive dataset from the country’s largest online complaint platform. Research Findings/Insights: Analyzing 22,644 firm-year observations from 2018 to 2023, we find that politically connected firms experience significantly fewer customer complaints. A one-unit increase in political connection strength is associated with a 9% reduction in complaints relative to the sample mean. This effect operates through two primary mechanisms: a reputation-motivation channel and a financial resource channel. The mitigating effect is more pronounced for firms in highly marketized regions, those with higher advertising expenditures, companies facing greater earnings pressure, and those with lower tangible asset ratios. Theoretical/Academic Implications: Our study contributes to the literature on political connections and corporate governance by demonstrating how political capital translates into tangible consumer experience advantages. It also advances research on the determinants of customer complaints by highlighting the role of internal governance mechanisms, particularly managerial political ties. Our findings support the Corporate Reputation and Financial Resource Hypotheses while challenging alternative explanations based on regulatory shielding or managerial complacency. Practitioner/Policy Implications: For corporate leaders, our results underscore the importance of reputation management and quality investment, particularly when political connections are absent. Policymakers should consider strengthening public monitoring institutions to reinforce reputational incentives across markets. Investors may use customer complaints as an indicator of product quality and operational stability in their investment decisions.

Recent technological advancements have enabled the emergence of business organizations fully managed by algorithms, such as decentralized autonomous organizations (DAOs) or through artificial intelligence (AI), as observed in China’s online food delivery sector. These organizations are collectively referred to as algorithm-managed firms (AMFs). Given machines’ capabilities in data collection and analysis, human directors are increasingly being replaced by algorithms or AI in specific sectors. This article contends that algorithms can effectively take over human directors’ managerial, monitoring, and mediating roles. The diminishing role of human directors raises certain concerns of stakeholder protection. Unlike human directors, algorithm directors or managers would not consider stakeholders’ interests unless clearly instructed to do so. However, the algorithm supplier and the AMFs may lack the incentives to fully consider stakeholders because they do not always internalize the social costs. To address the challenges of AMFs, policymakers need to consider different regulation strategies. First, they must choose between command-and-control regulations and target-based regulations. Command-and-control regulations often do not work well because regulators lack enough information or control over complex algorithms. Instead of setting detailed technical rules, policymakers should adopt target-based regulations that let the algorithm balance various interests and regulate its own operations. Second, policymakers should decide between entity-based and algorithm-based regulations. Algorithm-based regulation is more suitable because it prevents companies from passing costs onto society. The state could consider regulating the composition of the board of directors of the algorithm supplier to ensure that they incorporate the concerns of stakeholders’ interests in the development of the algorithm. Additionally, corporate law doctrines that protect creditors and other stakeholders, such as piercing the corporate veil and limiting liability for corporate torts, must be revisited and modified because their foundational assumptions no longer align with the realities of AMFs.

This study examines the mean-reversion behavior of trading volume in China’s A-share market, with a focus on the speed at which abnormal surges dissipate. We compare two competing hypotheses: the stealth-trading hypothesis, where persistent volume reflects order-splitting by informed traders, and the informational-efficiency hypothesis, which interprets faster reversion as a sign of efficient information absorption. Using the Ornstein–Uhlenbeck (OU) model, we estimate the reversion speed for over 3,000 stocks and link it to firm- and industry-level characteristics. We find that trading volume is strongly mean-reverting, with over 98% of stocks classified as stationary. The OU model forecasts reversion speed with less than 7% error. Faster reversion is associated with larger size, higher analyst coverage, lower volatility, and greater liquidity. Notably, reversion speed increased after the 2006 IFRS reform but declined following Stock Connect, suggesting that stock market policies can influence informational efficiency. Our OU-based methodology offers a simple, observable proxy for monitoring how quickly markets process information. These results position trading volume as a core variable in market microstructure research and policy evaluation.

In emerging markets characterized by signiffcant information asymmetry, mitigat-ing firm-level risk is paramount for market stability. While the governance role ofinstitutional investors is known, the impact of their direct, on-the-ground engagementremains underexplored. This study’s objective is to investigate how institutionalinvestor site visits, a crucial hands-on governance mechanism, affect stock returnvolatility. Using a sample of Chinese-listed A-share firms from 2012 to 2022, wefind that frequent site visits significantly reduce firm-level stock return volatility.This risk-reduction effect is more pronounced for firms with greater agency problems,poorer ESG performance, and higher expropriation risk. Our analysis, robust toendogeneity concerns, indicates this effect is driven by improved external oversight.We conclude that direct institutional engagement is a vital channel for reducinginformation asymmetry, enhancing corporate governance, and ultimately promotingmarket stability by lowering investment risk.

We propose a time-varying framework for tail risk contagion based on conditional higher co-moments (Co-HCM), derived from a DCC-GARCH-MGH model that provides closed-form expressions for dynamic co-moments. Applying this CoHCM approach, we construct tail contagion networks across Belt and Road Initiative (BRI) stock markets. Our ffndings indicate that covariance-based metrics underestimate the ex-tent of epidemic transmission, while the CoHCM metrics reveal China’s pivotal role in spreading outbreaks and identify a distinct cluster of core transmission hubs, particularly during the 2015 Chinese stock market crisis. Dynamic contagion further exhibits cross-country heterogeneity that the Southeast Asian markets synchronize tightly with China during crises, while smaller and resource-driven markets display more inter-mittent contagion patterns. These ffndings highlight the importance of higher co-moment dependence for monitoring systemic risk in interconnected emerging markets.

This paper examines the impact of Exchange-Traded Fund (ETF) ownership on corporate earnings management. We find that ETF ownership is associated with a significant reduction in earnings management, and this result remains robust across a wide range of endogeneity tests and robustness checks. Further analyses reveal that ETFs exert a pronounced mitigating effect on sales manipulation, production manipulation, and expense manipulation. Mechanism tests indicate that ETFs curb earnings management by improving stock liquidity and strengthening external monitoring. We also find that the influence of ETFs is stronger in private firms, in firms with lower information transparency, and in firms with CEO duality, suggesting that ETFs serve as a more prominent external governance force when internal governance mechanisms are relatively weak. Overall, this study enriches the literature on the economic consequences of ETFs and provides new empirical evidence that financial innovation in emerging markets can help alleviate the information risk faced by investors.

We construct the China Crude Oil Volatility Index (CNOVX)—the first model-free, optionimplied measure of forward-looking oil price risk for China—using INE crude oil options from 2021 to 2024 and an adapted CBOE methodology that accounts for sparse strike availability via smooth interpolation and extrapolation. Our results show that CNOVX increases with trading activity in the futures market, declines with option volume, and is strongly predicted by the 30-day realized variance of the SC crude oil futures contract. External shocks, including the Russia–Ukraine conflict and the Geopolitical Risk Index, significantly elevate CNOVX levels. During the COVID-19 pandemic, mortality risk intensifies the volatility-amplifying role of futures trading and strengthens the volatility-dampening effect of options, while confirmed case counts have weaker influence. We further document a pronounced asymmetric leverage effect: negative futures returns raise CNOVX more than positive returns of equal size. However, volatility feedback effects are negligible, as changes in implied volatility respond primarily to contemporaneous market conditions. Overall, CNOVX serves as a timely and informative benchmark for monitoring risk in China’s evolving crude oil derivatives market, with valuable implications for investors, hedgers, and policymakers.

This paper examines how auction design can unintentionally facilitate bidder collusion in land market. Departing from the dominant view that attributes low land concession revenues to corruption, we highlight how features of auction structure enable bidder-side collusion, suppressing sale prices. Using a dataset of land auctions from 15 Chinese cities (2006–2016), we find that two-stage (listing) auctions are significantly more susceptible to collusion than one-stage formats. Empirical evidence shows that sales concluding at the (secret) reserve price occur disproportionately in two-stage auctions, even after controlling for land and market characteristics. We argue that the transparency and sequencing of two-stage auctions, while designed to enhance fairness, inadvertently reduce monitoring costs and facilitate tacit bidder coordination. Our findings underscore the need to jointly consider auction format and reserve price policy in designing land sales to enhance market efficiency and mitigate collusion risks.