This paper investigates how government fiscal constraints transmit to the private sector through procurement. We exploit three rounds of VAT rate cuts in China (2017–2019) as exogenous shocks to local government revenues. Combining city-level fiscal pressure measures with 9,189 procurement contracts from A-share listed firms, we construct a firm-year exposure index weighted by procurement volumes across cities. We find that exposure to fiscally stressed government buyers significantly depresses firm valuation: a one-standard-deviation increase reduces Tobin's Q and price-to-sales ratios by 5.3% and 4.3%, respectively. This effect concentrates among private firms, those lacking industrial policy support, and firms with lower rent-seeking expenditures—precisely those with weaker bargaining power against government counterparties. Beyond valuation, such exposure leads to a subsequent deterioration in firm fundamentals, characterized by tightened liquidity constraints, reduced investment and financing, and worse information disclosure over a three-year horizon. Land finance partially buffers these effects. Our findings highlight an unintended micro-level consequence of macro fiscal policy: expansionary tax cuts designed to stimulate the private sector may inadvertently harm firms by weakening the government's capacity to fulfill procurement payments.

This paper studies how air pollution shapes offline cashless spending in China. Using monthly transactions from 118,698 merchants in 332 cities from 2019 to 2023, we find that higher pollution raises cashless spending. Instrumental variable and regression discontinuity designs confirm a causal effect. The increase comes mainly from more frequent but smaller purchases and greater participation by new customers. Spending also rebalances from postponable durables toward high-frequency, proximity-based categories, while durables respond little. These results uncover a behavioral channel whereby poor air quality shifts the margins and the composition of offline cashless commerce.

在我国当前低利率环境下，债券收益率持续下行，多元化资产配置的战略意义愈发凸显。本文基于桥水全天候理念，构建了适用于中国投资者的宏观因子增广Black-Litterman（ABL）模型，将宏观信号嵌入传统Black-Litterman（BL）模型的观点矩阵，同时整合风险平价先验基准，有效缓解了传统BL模型参数敏感性高及经济解释性不足问题。基于2012-2024年股债商汇四大类14项资产的回测表明，ABL模型实现了17.7%的年化收益和0.66的夏普率，优于传统BL模型及其他常用基准，且在波动率和最大回撤等风控维度更为稳健。ABL模型为资产配置提供了兼具理论创新与实践价值的参考方案。

可转债是上市公司重要的融资工具，其强制赎回条款在实践中可能被上市公司利用，通过操纵股价满足强制赎回条件，以便加速转股进程。基于2006-2025年中国A股市场数据，本文分析了可转债强制赎回背景下的股价异动现象。研究发现：在强制赎回条件触发的关键窗口期，正股价格出现显著异常拉升，强制赎回公告后则迅速反转，呈现“拉高达标”的“倒V”型反转特征；面临较高偿债压力和融资成本的发行人，更倾向于通过市场操纵推动股价达到强赎条件；微观交易数据显示，临近强赎节点时，市场买卖失衡、知情交易增多及大额交易增加，验证了主力资金通过短期内大量买入推升股价的操纵机制。本文揭示了可转债强制赎回条款可能诱发的道德风险，为完善市场制度设计和保护中小投资者权益提供了实证依据。

This study examines how global turbulence factors shape volatility spillovers among emerging stock markets through the lens of risk cycles. We find that emerging market connectedness exhibits clear regime heterogeneity across risk cycles, while also preserving several persistent structural patterns. Specifically, trade policy uncertainty (TPU) and economic policy uncertainty (EPU) serve the dominant drivers during risk outbreak and risk accumulation periods, respectively. Meanwhile, sustainability uncertainty (ESGUI) consistently plays a leading driver role in both regimes, while physical climate risk plays a comparatively limited role. Furthermore, the effects of these core turbulence factors are nonlinear and threshold-dependent, highlighting the importance of accounting for risk cycle heterogeneity and nonlinear dynamics when assessing emerging market risk transmission.

在我国资本市场规模持续扩张的背景下，证券虚假陈述等违法行为严重损害中小投资者权益、侵蚀市场诚信根基。传统责任认定依赖欺诈市场理论，面临因果关系举证难、损失计算偏差、追责靶向性弱等问题，导致责任划分在相当程度上依赖经验判断与自由裁量。本文锚定“计算正义”，认为在高度依赖数量判断的虚假陈述案件中，正义不仅体现为结果补偿，更取决于责任计算过程本身的透明性、可解释性与可复核性。在此理论立场下，文章提出基于穿透式监管的证券虚假陈述精准责任模型，通过整合司法大数据与AI算法，实现违法资金溯源、违法所得量化及“首恶”与“帮凶”责任比例精准划分，系统论证其法理基础、技术架构与法律合规可行性，为虚假陈述行政和解、先行赔付及司法审判提供兼具解释力与可操作性的新体系，推动投资者保护从“形式公平”向“实质正义”的进阶。

This study investigates the role of contextual cues in memory-based decision-making within high-stakestrading environments. Using trade records from a large Chinese brokerage firm and a novel dataset on COVID-19 quarantines, we find that quarantine periods trigger the recall of previously traded stocks, increasing the likelihood of subsequent orders for those stocks. The observed patterns align more closely with similarity-based recall than with alternative channels. Welfare analysis reveals that these memory-induced trades lead to an annualized loss of approximately 70 percentage points for the representative investor’s portfolio. We also find evidence at the market level: when the geographical distribution of quarantine risks is recalled, the probability of recalling the cross-sectional stock return-volume distribution from the same day increases by 1.6 percentage points. This study provides causal evidence from a real-world setting for memory-based theories, particularly similarity-based recall, and highlights a novel channel through which COVID-19 policies affect financial markets.

This paper investigates how foreign institutional investors, specifically Qualified Foreign Institutional Investors (QFIIs), influence the investment strategies of Chinese mutual fund management companies (FMCs) in which they hold shares. By analysing panel data from 1,766 mutual funds managed by 44 foreign-invested FMCs in China between 2005 and 2021, we explore whether QFII-invested FMCs (Q-FMCs) learn more from their domestic counterparts (D-FMCs) than other foreign-invested FMCs (NQ-FMCs). Our findings show that Q-FMC-managed mutual funds exhibit portfolio allocations more closely aligned with local DFMCs than those managed by NQ-FMCs. This imitation is particularly pronounced when selecting new stocks, enhancing portfolio performance, but not when rebalancing existing positions. Additionally, Q-FMCs trade more actively than NQ-FMCs. Robustness checks confirm these results across various ownership structures, fund characteristics, market conditions, and regulatory changes. These findings highlight the dual role of QFIIs as both investors and learners in China’s evolving financial landscape, offering insights into how foreign capital integrates into emerging mutual fund markets, informing regulatory policy aimed at fostering cross-border financial development.

We exploit a unique financial regulatory tool with data-governance functions as a quasi-natural experiment to explore the determinants of bank risk-taking. The paper finds that Examination Analysis System Technology (EAST) reduces bank risk-taking. This result is more pronounced in banks with higher capital adequacy ratios and higher liquidity levels. We also find that the inhibitory effect of EAST on bank risk is more significant for banks in eastern regions and listed banks. Our findings highlight the positive impact of data regulation on promoting financial stability.

在实现“双碳”与共同富裕目标并进的背景下，环保规制的公平后果日益受到关注。本文以2013、2014与2016年分批启动的碳排放权交易试点为准自然实验，基于2000—2023年中国区县面板数据，系统评估市场型环保规制的分配效应。结果变量方面，本文使用区县夜间灯光构建的不平等指标（基尼、泰尔、阿特金森）刻画县域经济活动分布，并以县域城乡居民收入对数差距作为补充。识别策略方面，除区县与年份双向固定效应的TWFE-DID外，进一步引入适用于分批采用的更强识别方法：（1）Sun-Abraham分组事件研究用于动态效应检验并规避传统事件回归在异质处理效应下的加权偏误；（2）Callaway-Sant’Anna ATT(g,t)在“尚未受处理/从未受处理”对照组框架下估计分组—时期平均处理效应；（3）合成双重差分（SDID）同时估计单位权重与时间权重，以匹配处理前趋势并降低对严格平行趋势的依赖。研究发现：在TWFE-DID下，试点显著降低了县域夜间灯光基尼与阿特金森指数；更强识别（ATT(g,t)、SDID）在城市层面同样指向夜间灯光泰尔指数的下降，但幅度更为温和。机制检验表明，试点显著降低城市单位GDP能耗，支持“绿色转型—要素再配置—分配格局改善”的作用链条。