实体经济盈利承压与虚实经济失衡的矛盾持续凸显，本文将产能约束与金融化 冲击纳入统一分析框架，依托 2010—2025 年中国省级工业面板与制造业上市公司 微观数据，运用面板门槛模型、多期连续双重差分模型与工具变量法，系统检验两 类结构性因素对工业利润的非线性冲击及盈利缓冲机制。研究表明，中国工业盈利 呈现显著的双阈值突变特征：金融化指数非线性临界阈值为 0.22，突破后利润挤出 效应呈非线性放大；产能利用率约束临界阈值为 0.75，低于该值后利润压制效应显 著增强，且金融化冲击强度显著高于产能约束。0.22 阈值对应企业财务费用占利润 总额的 22%，是付息能力的生死临界点，契合民间融资 2 分息极限、利息保障倍数 安全线与监管红色预警线。机制检验发现，阈值突破后金融化通过挤占实业投资、 抬升融资成本形成非效率分配冲击，传统产业升级、出口与逆周期政策的缓冲效应 全面失效。异质性分析显示，民营企业、传统制造业与中西部地区更易突破金融化 临界阈值，盈利受冲击程度更深。本文为划定金融化监管临界值、防范脱实向虚、 提振制造业盈利提供了量化依据与经验支撑。

This paper illustrates how firms with publicly disclosed political connections use subsidiaries to obtain preferential treatment in land markets. While the headquarters of politically connected listed firms pay land prices comparable to those paid by other firms, their subsidiaries receive discounts of 12.1%–13.2%. These discounts are more pronounced when land is acquired through less transparent methods, in regions with weaker institutional environments, and among private firms. The anti-corruption campaign launched in 2012 effectively mitigates corruption-related discounts, with the magnitude of the discounts negatively associated with campaign intensity. Additionally, larger discounts for subsidiaries are observed following greater charitable donations, suggesting a reciprocal relationship between firms and officials. Overall, the findings contribute to a broader understanding of how firms with publicly disclosed political ties use complex corporate structures to engage in rent-seeking behavior.

We use nearly a decade’s worth of panel data from European Union Chamber of Commerce in China business confidence surveys to analyse the deteriorating outlooks of EU firms in China from 2017 to 2025. All firms in China currently face challenges including slow profit growth and deflation. These circumstances have contributed to a rare drop of foreign direct investment into China over the last two years. However, certain challenges are particularly acute for foreign firms, including those from the EU. According to survey results, business sentiment among EU firms operating in China has never been bleaker. Respondents view their profitability, growth opportunities and competitiveness negatively, while fewer respondents than ever plan to expand their Chinese operations. Moreover, significant shares of respondents report recent increases in political pressure from the Chinese state and media, while nearly a third of respondents say they are siloing their Chinese operations, meaning separating them from other global activities. Disaggregated by size, sector, and years of operation in China, insightful differences emerge between the business strategies of EU firms. We broadly classify these into four categories: doubling-down, hedging, hibernating and ready to exit. EU policymakers should consider how to address the challenges EU firms in China face, such as asset-heavy sectors being ‘stuck’ in China and smaller firms lacking the capacity to operate at a loss in China’s market. The EU might need to facilitate transitions for these companies, helping them to reduce exposure to China and diversify into other emerging markets.

This study documents a novel, culturally embedded calendar anomaly in the Shanghai Composite Index (SSE Composite) derived from the Nayin (纳音) Five Elements system—a traditional Chinese sexagenary calendrical framework. Utilizing daily data from 1990 to 2025, the analysis reveals a significant correlation between elemental two-year periods and market performance. Key findings include: Earth-Element Dominance: Earth periods exhibit a 100% positive return rate (4/4) with a mean return of +123.4%. The effect size is substantial (Cohen’s d=1.50) compared to non-Earth periods. Metal-Element Declines: Metal periods universally display a structural peak-and-decline morphology, with an average −30.4% late-cycle decline. Water-Element Momentum: Water periods systematically mirror the directional momentum of their predecessors with 100% accuracy (3/3). These patterns fail to replicate in the S&P 500, suggesting a unique cultural-behavioral channel where traditional metaphysical cycles modulate investor sentiment in the Chinese market. This research provides the first empirical validation of Nayin-based cyclicality in financial asset pricing, offering a predictive framework for institutional and individual investors focused on the China-specific market. Keywords: Calendar anomaly, Chinese traditional calendar, Nayin Five Elements, Shanghai Composite Index, Cultural behavioral finance, Sexagenary Cycle, Market Sentiment Declaration of Interest The author declares no conflict of interest. To ensure the objectivity of this research, the author further declares that he holds no active personal trading positions in the securities discussed. The author's personal trading account has been inactive with zero transactions over the past five years.

We propose the AI Narrative Gap as a novel firm characteristic—the systematic divergence between a firm’s AI strategic narrative intensity and its subsequent AI capital expenditure commitment—and document its capital market consequences. Using Chinese A-share listed firms from 2015 to 2022, we show that firms with a wider AI Narrative Gap attract significantly more optimistic and less accurate analyst earnings forecasts. These distorted expectations, in turn, predict lower subsequent stock returns, lower industry-adjusted abnormal returns, and weaker future accounting performance. A double-sort portfolio placing firms simultaneously in the highest tercile of the AI Narrative Gap and highest tercile of analyst optimism earns a mean return 22.8 percentage points below that of the lowest tercile on both dimensions (t = −5.10). The return reduction in the AI Narrative Gap coefficient is attenuated but not eliminated after controlling for optimism, consistent with a partial expectation-distortion channel. Collectively, these results establish the AI Narrative Gap as a cross-sectionally informative firm characteristic that captures the credibility of a firm’s AI strategic identity, with systematic implications for analyst expectations and asset prices.

We posit and demonstrate that, in China’s retail-dominated market, quantitative trading over-relies on non-fundamental signals, thereby crowding out fundamental information from stock prices and increasing crash risk. Using trading data from quantitative mutual funds and Chinese A-share firms during 2009-2023, we find that greater exposure to quantitative trading is associated with higher future crash risk. Mediation analysis further reveals that reduced information efficiency constitutes a key channel through which quantitative trading elevates crash risk. The effect is stronger for stocks with more retail investors, consistent with our proposed mechanism. Overall, we identify a novel potential risk of quantitative trading in underdeveloped emerging markets.

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 investigates whether firms’ overtime intensity affects the cost of debt financing. Using satellite-based night-time light data for Chinese listed firms between 2013 and 2022, we construct an objective measure of weekday overtime that captures firms’ operational effort and capacity utilization. We find that higher overtime intensity is associated with significantly lower bond offering yield spreads. The effect is stronger among smaller, less-followed, less-profitable, and non-AAA-rated issuers, consistent with an information-asymmetry channel where investors rely more on observable operational behavior when hard information is weaker. The findings suggest that overtime functions as a priced form of soft information in debt markets, offering new evidence that real-time operational signals influence credit risk assessment.

This study investigates how venture capital (VC) reputation affects initial public offering (IPO) exits in the Chinese VC market using a two-sided matching mechanism. Research that distinguishes the sorting and influence effects of VCs in the Chinese market is lacking. To address this gap, Chinese VC transaction data, comprising 3,606 VC firms and 8,173 investment transactions, was used to construct a structural econometric model. The Markov Chain Monte Carlo Bayesian estimation techniques were employed to identify the sorting and influence effects of VC reputation. We demonstrate that the likelihood of IPO exits is considerably increased by VC reputation, whereas historical investment experience has a dampening effect on exit outcomes. The IPO success rates are significantly higher for firms in the biotechnology, electronics, medical, and late-stage industries. The difficulty of IPO exits increases with investment age. Compared to influence effects, sorting effects were the dominant mechanism. VCs with a high reputation systematically selected firms with potential advantages, such as high-quality management teams, to promote IPO success. This study’s novelty lies in its application of an endogenous two-sided matching solution to the Chinese VC market. Using a structural model, we discovered the importance of the reputation sorting effect in the Chinese VC market and refined the VC’s investment preferences in high-tech industries. This study’s practical significance lies in the findings that enterprises must pay attention to the sorting capabilities of VC institutions, the government can guide capital flows to efficient exit industries, and VC institutions should optimize the resource allocation structure.

Prevailing research, assuming developed financial markets, concludes that Chinese firms heavily rely on “short-term credit for long-term investment.”We challenge this view, arguing that China's vibrant informal financial system provides crucial alternative funding. Consequently, the severity of this maturity mismatch is likely overestimated. To investigate this, we examine strategic alliances as a representative informal institution. Our analysis confirms that such alliances significantly mitigate maturity mismatch, revealing that they enhance information sharing and reduce transaction costs. This provides initial evidence of informal institutions' critical role in addressing this issue. Given the prevalence of similar arrangements in China—like private lending and inter-corporate financing—our findings highlight the need to look beyond formal systems. This perspective not only recalibrates the understanding of corporate financing in China but also opens ample avenues for future research on informal finance's role in emerging economies.