We employ a time-varying parameter vector autoregression (TVP-VAR) joint connectedness approach to study the dynamic risk spillover effects between cryptocurrencies and China’s financial market, further exploring the impact of cryptocurrencies on China’s financial market. Our results show that there is asymmetric risk transmission between cryptocurrencies and China’s financial market, and the risk spillover effect is very weak. Specifically, the spillover of cryptocurrencies to China’s financial market is significantly stronger than the spillover of China’s financial market to cryptocurrencies. Cryptocurrencies have a stronger spillover effect to China’s exchange rate and gold. The net spillover effect of cryptocurrencies is weakening over time. Overall, the return spillover impact of cryptocurrencies on China’s financial market is greater than the volatility spillover impact, and the degree of impact of different cryptocurrencies is heterogeneous. This study provides some reference and guidance for cross-market investment portfolios and the regulation of China’s financial market.

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This paper investigates whether regional negative public sentiment associated with extreme non-financial social shocks (e.g., violence or crime) will affect the resident firms’ M&A announcement return. Using a sample of 3,200 M&A deals in China, our empirical results consistently show that M&A announcement return is significantly lower after the firm’s headquarter city has experienced negative social shocks. We further find that better CSR performance helps to mitigate the impact of these negative shocks. Overall, we show that firm operations will be largely affected by the resident environment and location, and better CSR performance acts as an effective risk management strategy.

To specify the peer effects that affect influencers’ sponsored content strategies, the current research addresses three questions: how influencers respond to peers, what mechanisms drive these effects, and the implications for social media platforms. By using a linear-in-means model and data from a leading Chinese social media platform, the authors address the issues of endogenous peer group formation, correlated unobservables, and simultaneity in decision-making and thereby offer evidence of strong peer effects on the quantity of sponsored content but not its quality. These effects are driven by two mechanisms: a social learning motive, such that following influencers emulate leading influencers, and a competition motive among following influencers within peer groups. No evidence of competition motive among leading influencers or defensive strategies by leading influencers arises. Moreover, peer effects increase influencers’ spending on in-feed advertising services, leading to greater platform revenues, without affecting the pricing of sponsored content. This dynamic may reduce influencers’ profitability, because their rising costs are not offset by higher prices. These findings emphasize the need for balanced strategies that prioritize both platform growth and influencer sustainability. By revealing how peer effects influence competition and revenue generation, this study provides valuable insights for optimizing content volume, quality, and financial outcomes for social media platforms and influencers.

本文深入探讨了股票人气对公司市值的影响机制及其双面效应。研究表明， 高涨的市场关注度能够通过改善融资条件、提升并购议价能力和拓展业务机会等 渠道，显著提升公司市值并反哺实体业绩。典型案例分析显示，融发核电因涉足 “可控核聚变”领域引发游资追捧，中毅达则凭借化工涨价题材获得资金青睐，二 者均在短期内实现市值快速攀升。然而，人气炒作也伴生着显著风险：当市场关 注缺乏基本面支撑时，极易诱发信息披露违规、内幕交易及操纵市场等违法违规 行为，招致监管处罚甚至退市风险。规范市值管理行为、强化信息披露质量、平 衡投资者关系与合规底线，是上市公司实现人气价值可持续转化的关键路径。

This paper examines how the integration of artificial intelligence (AI) and big data affects banking operations, emphasizing the crucial role of big data in unlocking the full potential of AI. Leveraging a comprehensive dataset of over 4.5 million loans issued by a leading commercial bank in China and exploiting a policy mandate as an exogenous shock, we document significant improvements in credit rating accuracy and loan performance, particularly for SMEs. Specifically, the adoption of AI and big data reduces the rate of unclassified credit ratings by 40.1% and decreases loan default rates by 29.6%. Analyzing the bank's phased implementation, we find that integrating big data analytics substantially enhances the effectiveness of AI models. We further identify significant heterogeneity: improvements are especially pronounced for unsecured and short-term loans, borrowers with incomplete financial records, first-time borrowers, long-distance borrowers, and firms located in economically underdeveloped or linguistically diverse regions. Our findings underscore the powerful synergy between big data and AI, demonstrating their joint capability to alleviate information frictions and enhance credit allocation efficiency.

Under the guidance of the dual-carbon target, the development of the carbon financial system is of great significance to compensate for the gap between green and low-carbon investment. Considering the current state of the development of carbon financial system, China has initially formed a carbon financial system, including participants, carbon financial products and macro and micro operation structures, but the system is still in the initial development stage. Given the current restrictions on the development of carbon finance, it can be seen that there are still problems such as unreasonable economic structure, insufficient market construction, single product category, low utilization rate and urgent construction of relevant judicial guarantee system. Therefore, the system should be improved at the economic level and the legal level. The economic level includes adjusting the layout of economic development structure, strengthening the construction of market infrastructure, encouraging the diversification of carbon financial products and strengthening publicity and education promotion strategies. The legal level includes improving the top-level design, formulating judicial interpretation to promote carbon financial trading, promoting commercial law amendment, and promoting the linkage mechanism between specialized environmental justice and carbon finance and other safeguard measures. Finally, improving the carbon finance system is required to promote and protect the orderly development of carbon finance. To promote the reform of the pattern of economic development, the concept of ecological and environmental protection in the financial sector needs to be implemented to form an overall pattern of pollution reduction, carbon reduction and synergistic efficiency improvement.

Despite nearly twenty years of privatization, mixed-ownership reform has been the mainstay of SOE reform in China in recent years. This raises the question of whether the financial performance of mixed-ownership firms (Mixed firms) is better than private-owned enterprises (POEs). Although Mixed firms suffer more from government intervention, unclear property rights, and interest conflicts between state shareholders and private shareholders, they can also benefit from the external resources controlled by the state. Therefore, the performance of Mixed firms is still unclear. Collecting data from the Chinese A-share listed market, we divide the firms into POEs, Mixed firms controlled by the state (MixedSOEs), and Mixed firms controlled by the private sectors (MixedPOEs). Measuring profitability using ROA and ROE, we find that on average, POEs perform better than Mixed firms, and MixedPOEs have a higher profitability than MixedSOEs. Within Mixed firms, more state shares are related to lower profitability, and more private shares are related to higher profitability. Using the NBS survey data, we further find that on average, SOEs exhibit the lowest profitability, with MixedSOEs and MixedPOEs in the middle, and POEs have the highest profitability. We try to address the endogeneity challenge in several ways and get similar results. Overall, our analysis provides new evidence on the financial performance of mixed-ownership firms.

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A second-tier patent system with relatively low protectability standards has been adopted by many countries, but empirical evidence on how it is used by firms israre. Using Chinese patent data, we exploit “parallel filings” – where a second-tierpatent is filed simultaneously with an invention patent – to shed light on its usein practice. The data indicate that while parallel filings appear to be inventionswith a narrower scope, they are cited more frequently in the early years and morelikely to be licensed or transferred compared to inventions protected by standardpatents. We provide evidence that parallel filing is likely a strategic choice forshort-life-cycle technologies that achieve high value early in their lifetime but decayfast. The rapid issuance of the second-tier patent facilitates knowledge diffusionand technology transfer, thereby helping the patentees capitalize on the value of fast-moving technologies. This study provides some much-needed empirical evidenceon how the quick procedure of the second-tier patent system serves short life-cycletechnologies.