Focusing on the macroeconomic downside risk under uncertainty shocks, we begin by refining the measurement of China's internal and external economic uncertainties, and the adjustment for extreme outliers caused by the COVID-19 pandemic is effective in enhancing the accuracy of uncertainty measurements. We then employ a quantile vector autoregression model to investigate the relationship between internal and external economic uncertainties and China's macroeconomic downside risk. The results indicate that when the economy is experiencing slow growth, the negative effects of internal uncertainty shocks become more pronounced. A high-intensity internal uncertainty shock may significantly increase the downside risk of China's economic growth. External uncertainty shocks can not only exert a direct impact on the downside risk of China's economy but also induce indirect disturbances by amplifying the internal uncertainty.

We propose a new framework for pricing illiquidity risk in China's stock market. Grounded in market microstructure and behavioral finance theory, our time-weighted intraday Amihud (TIAM) measure isolates true trading-driven price impact and empirically outperforms traditional daily proxies. A rigorous dissection of the TIAM premium reveals that its characteristics of long-horizon persistence and strong countercyclicality are consistent with compensation for systematic risk, not transient mispricing. We distill this premium into a size-neutral Intraday Illiquidity Factor (IML) that earns a significant alpha against established asset pricing models. We demonstrate that our friction-based illiquidity factor provides a powerful, risk-based explanation for a substantial portion of the size and sentiment anomalies, reframing them as manifestations of a more fundamental, structural risk. Our findings establish intraday illiquidity as a distinct dimension of priced risk, crucial for understanding the asset pricing dynamics of emerging markets.

To address the limitations of traditional systemic risk indices in measuring nonlinearity and network interdependence, we introduce ESRISK, a novel systemic risk measure that incorporates ensemble learning and risk spillover networks. Our approach can effectively analyze the complex nonlinearity in high-dimensional data, enabling more accurate quantification of systemic risk in China's financial system. Comprehensive evaluations reveal that ESRISK outperforms prevailing systemic risk measures, particularly in predictability, accuracy in measuring systemic risk, and effectiveness in early warning detection of systemic events. Moreover, ESRISK demonstrates superior predictive power for macroeconomic downturns. Our findings highlight the importance of applying machine learning methods and considering inter-institutional spillovers when measuring systemic risk in China's financial ecosystem.

Examining how corporate environmental, social, and governance (ESG) performance impacts the sustainability of green innovation holds significant theoretical and practical value for achieving China's "dual carbon" goals and advancing corporate sustainability. This study contributes by providing novel empirical insights into the mechanisms and heterogeneous effects of ESG on sustained green innovation, addressing gaps in understanding ESG's role in emerging markets like China. Using data from Shanghai and Shenzhen A-share listed firms (2009-2023), this study investigates the relationship between corporate ESG performance and sustained green innovation, revealing three key findings. First, corporate ESG performance significantly promotes sustained green innovation - a conclusion robust to rigorous sensitivity tests. Second, mechanism analysis confirms that strong ESG performance elevates innovation capacity by alleviating financing constraints and reducing agency costs, while stricter environmental regulations and higher levels of digital transformation further amplify ESG's positive impact. Third, heterogeneity tests demonstrate that ESG's effect is more pronounced in non-state-owned enterprises, non-high-pollution industries, growth-stage firms, and enterprises with higher ESG rating divergence. These insights offer critical theoretical and practical implications for ESG and innovation literature, as well as practical implications for ESG implementation and green policy design in China, guiding firms and policymakers toward more effective sustainability strategies.

This paper introduces an innovative dynamic asset allocation approach to hedge against panic sentiment and demonstrates that adopting such an anti-panic strategy can be beneficial. We first develop a novel measure of panic sentiment and analyze its spillover effects across major stock markets. The strategy’s diversification advantages in mitigating panic sentiment are then evaluated. Backtesting results reveal substantial long-term excess returns over benchmarks, with risk-adjusted metrics and statistical tests confirming the robustness of these results.

We propose a new systemic risk measure (MSRISK) for China using machine learning methods and the risk spillover index. Our method provides effective analysis of higher-dimensional data and captures the nonlinearity of systemic risk, thus allowing for a more accurate measurement of Chinese systemic risk. Through comprehensive assessments, MSRISK significantly outperforms existing systemic risk measures, particularly in terms of its forward-looking forecasting capabilities, accuracy in systemic risk quantification, and proficiency in early warning detection of risk events. Moreover, MSRISK demonstrates superior predictive ability for macroeconomic downturns. Our findings highlight the importance of applying machine learning methods and the consider of inter-institutional spillovers when measuring systemic risk in China's financial ecosystem.

This study extends extant discussions on regional integration by exploring risk spillovers between news-based panic sentiment and stock market volatility among Regional Comprehensive Economic Partnership (RCEP) members during the COVID-19 pandemic. We innovatively estimate quantile-based spillover indices in both time and frequency domains and construct the multi-layer network. Both static and dynamic risk spillover patterns in the "RCEP panic-stock network" are outlined. It is found that risk spillovers are predominantly transmitted from the "panic-layer network" towards the "volatility-layer network". Besides, regression analyses are employed to investigate whether general features of COVID-19 media reporting affect the spillovers of panic sentiment at the country level. The results show that the magnitude of panic spillovers tend to be positively associated with overall media coverage and negatively with overall media sentiment, especially at the middle and lower quantiles.

The IPO supply moves closely with investor sentiment, as the Chinese government regularly uses it as an intervention tool to offset sentimental demand for stocks. This novel sentiment measure allows us to uncover a significantly negative relationship between sentiment betas and expected stock returns in China's stock market. Earnings extrapolation causes overvaluation of high sentiment-beta stocks, and short-sale constraints and the disposition effect prevent immediate correction of the mispricing. Moreover, the sentiment-beta anomaly mainly concentrates on big state-owned enterprises with close ties with the government. The result is consistent with the argument that policy noise in market interventions is a crucial driver of mispricing in China's stock market.

本文首次构建金融社交媒体信息指标(FI),研究了金融社交媒体信息对股票横截面收益率的预测力以及对资本市场异象的影响.研究发现:金融社交媒体信息与股票未来横截面收益率间存在明显的单调递增特征,并且在控制多种风险或者情绪定价因子后上述特征仍然稳健.金融社交媒体信息对股票收益率的预测力体现了信息经由金融社交平台进入股价的过程.金融社交媒体信息将捕捉到的股票基本面信息注入市场,然而受到市场套利成本的阻碍,信息进入股价的过程被拉长,导致金融社交媒体信息对股票收益率的预测力呈现持久性.本文的实证证据进一步发现,金融社交媒体信息提供的股价信息有助于投资者识别并消除妨碍市场合理运行的市场异象,从而有效提升资本市场运行效率.本文研究结论对于进一步推动互联网建设、加速互联网与资本市场融合建设、促进资本市场高质量发展具有重要的理论意义和现实价值.

This study examines arbitrage asymmetry effect on six well-known anomalies in China's stock market. Using a comprehensive mispricing index constructed based on four popular mispricing measures, we show that anomalies are much more pronounced among overpriced stocks, but weaker or even reversed among underpriced stocks. Results also hold after controlling for several existing mispricing proxies and are stronger among stocks with high arbitrage costs. Our finding suggests that arbitrage costs that mostly result from short-sale constraints hinder correction of overpricing and increase the inefficiency of the stock market.

本文以新《环保法》实施作为准自然实验,采用双重差分模型探究环境规制对重污染企业融资约束的影响及其作用机制.研究发现,新《环保法》的实施显著缓解了重污染企业融资约束;截面异质性分析显示,新《环保法》对重污染企业融资约束的缓解作用仅在小规模企业和银行业发展较好、污染程度较高、法律环境较差的地区显著;经济机制分析表明,新《环保法》通过降低代理成本、缓解信息不对称、促进企业社会责任履行,缓解重污染企业融资约束.本文结论既拓展了环境规制对企业影响的研究边界,也为"双碳"目标下中国实现生态保护与经济增长的协同发展提供了理论支撑和经验证据.

为深入考察政府创新扶持政策的作用效果与内在机理,本文以《国家中长期科学和技术发展规划纲要(2006-2020年)》中提出的研发补助政策和税率优惠政策为研究对象,采用基于倾向得分匹配的双重差分法对政府创新扶持政策的双重效应进行识别.研究发现,政府研发补助政策兼具"前期激励"与"后期奖励"效应,显著提高了企业创新能力,而税率优惠政策并不能促进企业创新.进一步分析显示,持续且平稳的研发补助额度、企业经营地理分散化和外部创新环境显著强化了创新扶持政策对企业创新的积极作用.本文不仅弥补了现有研究对政府创新扶持政策内在动机和潜在机制的忽视,还将研究视角由"政府之手"扩展到"市场之手",对政策影响企业创新能力的逻辑链条进行了必要补充.本文研究揭示了政府创新扶持政策实施的内在规律,为我国应对日益激烈的国际竞争,实现创新驱动发展战略,提供政府扶持驱动企业创新的理论支撑与政策建议.

本文以2011-2018年中国A股上市公司发行的一般公司债为样本,探究了中债估值跳跃对债券信用利差的影响及作用机制,以此说明中债估值对债券信用风险的识别作用.研究发现:中债估值跳跃能够显著提高债券信用利差,其中,中债估值上跳降低了信用利差,下跳提高了信用利差,且相对于上跳,下跳对信用利差的作用更大.异质性分析发现:中债估值跳跃对信用利差的作用在机构投资者中较大,同时在信息不对称性较严重、流动性较差及违约风险较高的债券中也较大.进一步研究发现:中债估值跳跃不仅包含了公共信息,还含有私有信息,并能改善股票分析师预测表现.本研究说明中债估值能够识别债券信用风险,具有信息含量,对于债券市场信息环境建设和系统性金融风险防范具有重要意义.

We present a model in which an insider (i.e., manager or CEO) and an informed outsider (i.e., financial analyst or professional) have heterogeneous beliefs on their shared information about a risky asset and analyze the insider's incentive to voluntarily disclose this information to the public. We find that with heterogeneous beliefs the insider and informed outsider exploit their shared information differently and this might give rise to the insider's voluntary disclosure of this shared information to the public to seek excess profits. Specifically, the insider is more likely to release the information to the public when she has a greater relative information advantage than the informed outsider and that the informed outsider is more optimistic in the shared information. Our findings shed light on why some firm insiders prefer to trade against informed outsiders while others prefer to drive informed outsiders out of trading through voluntary disclosure.

以2007-2018年中国上市公司发行的上市公司债为研究样本,本文考察了机构投资者持股对债券限制性条款设计的影响.研究发现:(1)机构投资者持股可以显著减少债券限制性条款的使用,机构投资者持股比例越高,债券限制性条款的使用越少;(2)机构投资者通过改善公司治理和信息环境,缓解了债券发行人与债券投资者之间的代理冲突,从而减少了债券限制性条款的使用;(3)当机构投资者非独立、持股稳定性较强、机构数量较少以及债券发行人为国有企业时,机构投资者对债券限制性条款的抑制作用更强.本文发现了机构投资者对债券市场的积极稳定作用,为债券限制性条款设计提供了理论依据,同时也肯定了中国背景下推动机构投资者发展的积极意义.

本文采用中国A股市场实施股权激励计划的上市公司为样本,基于断点回归分析方法,研究上市公司实际报告业绩在股权激励计划预定的业绩目标处聚集的现象,并对其产生的原因进行了分析.研究发现,实施股权激励计划的上市公司存在明显的业绩条件"踩线"达标现象,即实际报告业绩刚刚达到股权激励方案要求的业绩条件,并且基于目标棘轮效应和管理者参考点偏好效应两方面对其产生的原因进行了分析.本文还发现,随着行权限制的变化,短期权益激励能够抑制目标棘轮效应,长期权益激励能够增强目标棘轮效应和管理者参考点偏好效应,而且,管理者操纵报告业绩的行为具有连续性.本文首次验证了管理者参考点偏好效应能够解释管理者向上操纵业绩而产生的业绩聚集现象,从行为金融学的角度推进了公司股权激励的研究进展.本文研究结论支持2016年正式出台的《上市公司股权激励管理办法》的制定原则,也为政策制定者和上市公司如何进一步完善股权激励制度建设与方案设计提供了新的治理思路和决策依据.

本文使用2007-2017年中国A股上市公司数据,探讨股价信息含量是否能够影响分析师预测质量.研究发现:1)股价信息含量能够有效提升分析师预测质量,表现为伴随股价信息含量的提升,分析师的预测偏差,预测乐观度和预测分歧均显著降低,分析师跟踪人数显著增多.2)当公司机构持股比例越低,会计稳健性越强以及信息透明度越差时,股价信息含量对分析师预测质量的影响更强.本文的研究对于全面认识股价信息含量,促进分析师在资本市场信息中介作用的发挥以及资本市场的健康发展具有一定的理论和现实意义.

本文以中国A股非金融上市公司为研究对象,采用Baker et al.(2016)编制的“中国经济政策不确定性指数”,探讨经济政策不确定性对大股东股权质押决策的影响及其作用机制.研究结论表明,经济政策不确定性能够提高大股东股权质押的意愿及规模,上述影响在非国有企业和存在卖空限制的公司中更为显著.进一步地,影响机制检验发现融资约束和错误定价是经济政策不确定性影响大股东股权质押决策的两种渠道.此外,大股东在经济政策不确定性较高时进行股权质押将加剧系统性风险.本研究不仅为经济政策不确定性的微观经济效应提供了新的证据,同时也从宏观层面解释了大股东股权质押的影响因素.

提高企业生产效率是提升经济发展质量的核心动力,如何增强资源分配能力,提升投入产出效率,是目前我国经济转型期亟需解决的问题.本文以2000-2019年A股上市企业为样本,研究股票流动性对企业生产效率的影响和作用机制.研究结果表明:股票流动性有助于提高企业的资源分配能力,这主要是源于管理者学习和信息传递效应,高流动性的股票提高了企业特质信息含量,为管理者明确市场对企业的评价并改进生产决策提供依据.融资约束和代理冲突严重的企业更依靠股票流动性带来的信息参考和信息反馈作用,因此,股票流动性对企业全要素生产率的提升效果更显著.与国有、低杠杆的企业相比,股票流动性更能够促进非国有、高杠杆的企业提高投入产出效率.本文研究诠释了股票市场不仅仅是资金供给者,还作为信息提供者提高了企业的生产效率,也为金融体系如何更好地服务实体经济打开了新的思路.

近年来,A股上市公司实际控制人超额委派董事现象备受社会舆论和学术界关注.在分散股权时代,实际控制人超额委派董事在强化董事会控制权的同时,客观上维护了上市公司控制权的稳定,提升了董事会决策的一致性,为管理者专注于提升企业长期价值营造了相对稳定的内外部环境.基于此,本文以企业创新为着眼点,研究实际控制人超额委派董事是否影响企业创新,发现实际控制人超额委派董事促进了企业创新.机制分析显示,实际控制人超额委派董事通过延长职位任期和增加货币薪酬降低了管理者对技术创新的风险厌恶,进而提升了企业的创新水平.本文还发现实际控制人超额委派董事对企业创新的促进作用在不存在多个大股东、高技术企业中表现得更加明显.本文不仅丰富了企业创新影响因素及实际控制人超额委派董事经济后果领域的研究文献,而且对现实中通过控制权优化提高企业创新能力具有重要的实践价值.