菲利普斯经典分析体系诞生于低储蓄、直接融资的经济环境，将其套用于高储蓄经济体时，会出现明显的理论适配偏差。研究依托资金运行逻辑推导得到M1,t⋅Kt>QMt收益等价约束条件，据此搭建 LDR—K 双临界均衡分析框架，明确货币传导弹塑性断裂的定义与量化判定规则。面板实证结果表明，住户定活比（LDR）与实体收益倍数（K）的合理运行区间为 1.77∼1.83。当两项指标同步处于该区间，货币传导效率可提升4.3～4.8倍，M1/QM 将回归 1:2 的长期均衡水平。LDR 与 K 存在双向动态联动关系，居民存款结构主导短期传导，实体盈利水平决定中长期运行趋势。本文纠正了学界关于 M2/GDP、储蓄率与货币结构的三类认知误区，延伸了经典货币政策理论的适用范围。建议把 LDR、K 纳入央行常规监测指标，结合四类经济区制推行差异化调控，为高储蓄经济体搭建专属货币政策框架提供理论与实证依据。

既有研究普遍认为企业披露数据资产信息能有效降低股价同步性、提升资本市场定价效率。本文基于有限注意力理论，重新审视了数据资产信息披露对资本市场定价效率的影响。研究发现，数据资产信息披露的经济后果并非静态不变，而是随着市场整体披露密度的上升呈现出显著的边际递减特征。具体而言，在市场整体披露水平较低时，企业披露此类信息能有效吸引媒体报道、增加分析师追踪并吸引机构投资者持股，进而加速特质信息融入以降低股价同步性；然而随着披露的普遍化，同质化信息分散了投资者的注意力，弱化了上述机制。基于“龙虎榜”的准自然实验进一步证实，注意力的分散是导致披露效果发生变化的关键原因。异质性分析表明，即便在企业常规文本特质信息较少、地区信息传播环境优越或机构投资者注意力未被过度分散的情境下，这种因同质化披露引发的边际递减现象依然存在。本文拓展了有限注意力理论的适用边界，揭示了同质化信息对投资者注意力的分散作用，为理解数字化时代企业信息披露面临的“价值稀释”问题提供了新的经验证据。

中国式现代化的根基在县域，县域发展的核心瓶颈是金融供给系统性失灵与内生信用机制长期缺失。城乡二元结构导致县域农村产权先天残缺，叠加 20 世纪 90 年代县域集体经济结构性调整，本土产业支撑力持续弱化，部分地区长期依赖上级财政转移支付运转。转移支付作为外部资金，与本地资产增值、治理效能提升的联动性较弱，难以培育可持续内生动力。既有县域金融研究多侧重抵押品目录扩容，忽视估值修复的基础作用，难以破解资产沉睡与信用缺失的双重困境。本文以县域抵押品体系失灵为切入点，整合产权残缺、信贷配给、金融加速器三大理论，构建估值修复—边界扩容—信用创造递进框架。基于 2024—2025 年广东省权威数据及多地试点准自然实验表明：脱离估值修复的抵押品扩容易被信贷配给弱化；唯有补齐确权、估值、流转、处置全链条短板，方能盘活县域沉睡资产、转化为信用资本，夯实内生发展能力。

近年来，“宽货币、弱实体” 成为宏观调控面临的突出难题。本文利用 2014—2025 年中国 31 个省份的省级季度面板数据（1488 个观测值）展开实证检验，发现样本期内新质生产力与非新质领域的信贷产出效率保持相对稳定，并由此得到 E=0.17+0.49α 的线性货币效率关联。本文采用面板格兰杰因果检验、2SLS 工具变量回归以及 2018 年资管新规冲击的双重差分模型开展三重因果识别，同时结合效率均值敏感性分析与多维稳健性检验，结果表明，新质生产力信贷占比每提升 1 个百分点，宏观货币效率相应提高约 0.49 个百分点。根据浙江、江苏、广东三省的实际数据校验结果，经济稳态区间内模型估计值与真实值拟合程度良好，结论具备较强的现实解释力。优化信贷结构是化解 “宽货币、弱实体” 矛盾的核心路径，研究结论能够为货币政策由总量调控转向结构精准调控提供量化依据。

西方租售比、房价收入比模型在中国房地产市场长期存在适用性缺陷。本文立足宏观审慎监管视角，构建以 "套" 为计价单位、名义 GDP 增速与商品房整体交易率为双锚的 CMH 估值模型。依托 2000—2025 年官方公开数据，采用样本内拟合与样本外预测双重验证范式，精准识别房地产周期拐点并验证 CMH 收敛速率定律。本文确立双向宏观审慎阈值体系：以 0.60 作为防过热预警线，以 "交易率 1.0%+ 估值 0.40" 作为防过冷预警线，形成 "估值锚定上限、交易率监测底线" 的核心监测规则。实证结果表明，CMH 模型可作为房地产逆周期调控的量化工具，为落实 "房住不炒" 定位、实现市场平稳健康运行提供可复现的决策依据。

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 examine price discovery after irregularly scheduled macroeconomic announce-ments. Exploiting time variation in Chinese macro announcements released outside regular trading hours, this paper isolates the role of elapsed non-trading time in facilitating investor learning and price discovery upon market reopening. We show that longer non-trading intervals generate more efficient post-announcement price discovery, reduce information asymmetry, and diminish subsequent intraday return reversals. The mechanism operates through enhanced retail investor learning: during non-trading hours, retail investors actively acquire information, subsequently trade more aggressively, earn higher profits, and face reduced informational disadvantages at market opening. Our findings highlight that retail investor learning during non-trading hours levels the informational playing field among heterogeneous investors and improves price quality around irregularly timed macroeconomic announcements. These results have broader implications for emerging markets, which similarly feature irregular announcement timing and large populations of uninformed retail investors.

This study constructs a three-dimensional space model based on fund investment styles, using a sample of open-end equity and mixed funds from 2005 to 2021 to measure the degree of style convergence. The research explores how style convergence impacts fund managers’ window dressing behavior. The results indicate that, after accounting for the effects of fund performance, style convergence exacerbates window dressing behavior among fund managers. Specifically, this is reflected in fund managers increasing their holdings in winning stocks and selling off losing stocks, which indirectly highlights the intense competition within China’s open-end fund industry. The findings remain robust after a series of endogeneity and robustness tests. Further analysis reveals that style convergence contributes to the risk of client attrition, thereby intensifying the agency problem within the fund industry. The window dressing effect due to style convergence is particularly pronounced in funds managed by individuals with lower educational backgrounds, lower investment skills, smaller family sizes, and lower institutional investor ownership. The paper offers valuable insights into the agency problems arising from investment style convergence and provides guidance for mitigating fund managers' self-interested behavior.

This study investigates how mutual funds impact the stock market by ana-lyzing the relationship between mutual fund investment behaviours (holding and trading) and stock returns and realized volatility in the Chinese market. It is found that stocks widely held or bought by mutual funds can earn higher excess returns, and more importantly, the trading measures out-perform the holding measures, which is evident by the portfolio analysis and Fama-MacBeth regressions. Moreover, the proportional holding, pro-portional trading and shares trading measures positively and significantly predict future realized volatility. Meanwhile, a weak asymmetric effect in the share-trade measure is found.

Contrary to the U.S., Chinese stock markets exhibit negative overnight returns, which further decrease with information asymmetry. We demonstrate that China’s "T+1" trading rule, which prohibits same-day selling, exacerbates adverse selection for uninformed buyers by limiting them to react to post-trade information. Prices are hence initially discounted at opening and recovered by the market close, generating negative overnight returns that are inversely related to information asymmetry risks. Consistent with adverse selection, empirical evidence reveals lower overnight returns during market declines and high-volatility periods, with robust negative associations between overnight returns and information asymmetry proxied by ffrm size, analyst coverage, and earnings announcement proximity. A model is introduced to rationalize our findings. The framework also sheds light on China’s "opening return puzzle", the phenomenon that intraday price rises concentrate predominantly in the initial 30 minutes of trading, by showing how reduced adverse selection enables rapid price recovery during opening session.