This study empirically investigates the impact of dialect diversity on corporate investment efficiency under different levels of economic policy uncertainty. Our findings reveal that local dialect diversity enhances investment efficiency during stable periods, but this advantage significantly diminishes under high economic policy uncertainty. This reduction primarily arises from underinvestment and overly cautious decision-making by fragmented management during periods of turmoil. Further analysis reveals that this reduction is exacerbated by stronger internal governance, which emphasizes checks and balances, and mitigated by stronger external governance, which focuses on supervisory power. Our results remain robust when using alternative measures of main variables and employing topography as an instrumental variable.

We investigate the causal impact of a company's environmental and social (ES) risk on the borrowing costs of its peer firms (that share lending banks). Using a regression discontinuity design based on the voting outcomes of ES-related shareholder proposals in US public companies' annual meetings from 2005 to 2021, we find that the passage of ES-related proposals leads to an average increase of 38 basis points in the loan costs for peer firms in the subsequent year. The negative spillover is more pronounced for peers with lower bargaining power in their banking relations or having lower ex-ante ES scores, on credit lines rather than term loans, and during the earlier years, validating that banks indeed channel the spillover. Notably, the spillover is particularly significant if the peer firms locate in the same states as the focal firm, or when the proposals reflect a higher degree of disagreement between the proposing shareholders and the managers, or for loans issued by banks lacking prior incentives or expertise in pricing ES risks (``non-ES banks''). We interpret these findings as evidence that the passage of ES-related shareholder proposals releases new information related to peers' ES risks and especially raises the awareness of ES risks among non-ES banks, prompting them to adjust loan rates for their portfolio companies accordingly.

This study investigates how firms respond to restricted access to government information. Specifically, the Stop Trading on Congressional Knowledge (STOCK) Act, which limits the stock trading activities of government officials (hereafter referred to as politicians), reduces the willingness of politicians from federal executive branches to engage with firms. Utilizing this exogenous disruption in private communication, we employ a difference-in-differences approach to demonstrate that firms with significant government customers decrease the frequency of management forecasts more than other firms due to the STOCK Act. This reduction is more pronounced for firms where government sales are crucial to their performance and for those that serve as suppliers and government contractors. Further, the positive impact of the STOCK Act on voluntary disclosures is more significant for firms that ex-ante rely heavily on direct political engagements, as indicated by their discussions of political risk and political contributions, and for those expecting government support, as evidenced by higher competition levels within their industry. Conversely, the STOCK Act does not significantly affect the non-financial disclosures of these firms. Finally, consistent with findings on executive branch officers, our results indicate that congressmen are also involved in corporate communications and are effectively regulated on information exchange by the STOCK Act. Overall, these results justify the powerful supervisory impact of the STOCK Act on the U.S. government and capital market and help to facilitate a new U.S. government information disclosure policy for a fairer investment environment.

央国企在我国经济社会中除了创造经济价值和国家税收外，还承载着广泛的社会责任与企业担当。受行业属性、经营状况和政策因素等多方面影响，部分央国企长期存在市场估值偏低、投资者情绪低迷的问题。中国特色估值体系的提出与实践，有利于修复当前国企和非国企估值水平割裂的现状，对我国金融高质量发展具有重要意义。本文利用股吧文本、股票市场交易和公司股权数据，采用模糊断点回归设计，评估中国特色估值体系提出之后上市公司经营性质对于投资者情绪的影响。研究发现：（1）“中特估”在官方层面正式提出后，上市公司国有控股经营性质对个股投资者情绪有显著的提升作用；（2）该效应在日常消费品、工业和通讯服务三大行业和高市值公司较为明显，且在时间维度上具有短期滞后性和长期衰减性；（3）本文进一步发现，这一处理效应可能通过股息偏好机制发挥作用。本文的研究在一定程度上填补了对“中特估”效应定量分析的空白，有助于理解新形势下上市公司股权结构优化、混合所有制改革的实践，对引导市场投资者情绪也有一定的政策和企业决策参考价值。

为评价中国“价格型”货币政策的调控效果，本文基于企业面板数据全面考察了中国人民银行的公开市场操作对企业债券到期收益率和企业信贷融资成本的影响。首先，基于企业债券数据的实证研究表明，公开市场操作所形成的政策利率（以下简称 OMO 利率）对企业债到期收益率存在显著的正向乘数效应。其次，基于上市企业财务数据的估计结果显示，OMO 利率对企业信贷融资成本存在显著的正向传导效果。最后，非对称性的研究结果表明，OMO 利率上升对债券到期收益率的推升效果显著大于下降时的降低效果。本文的研究证实了，从实体经济角度而言，公开市场操作是高效率的货币政策实施工具，其所形成的OMO 利率是有效的货币政策测量指标。

This paper explores the impact of political network on insider trading activities in China. We find that stronger political network discourages insider trading. Such effect is more pronounced among long-standing and high-level connections, and persists in the events of M&A and public policy announcement when insiders may make profitable informed trading. This finding points to new cost of being politically connected. In exploring the underlying mechanisms, we confirm that the muted insider trading is related to preferable financial and policy support, and are more pronounced for SOEs in provinces with stronger market force and legal enforcement.

We investigate the effect of the Consumer Financial Protection Bureau’s 2015 disclosure of complaint narratives on reducing racial disparities in financial services. Employing a triple-differences approach that compares the performance of affected and unaffected financial institutions across communities with varying racial compositions, we find that post-disclosure, minority communities experience welfare enhancements. These include higher savings interest rates (amounting to over $50 million annually), reduced maintenance fees, and lower interest rates on auto loans and credit cards. The research emphasizes the broad impact of service quality disclosure in mitigating racial disparities in savings and lending markets.

In this paper, we show that only the systematic component of exchange rate expectations of professional investors is a strong predictor of the cross-section of currency returns. The predictability is strong in short and long horizons. The strategy offers significant Sharpe ratios for holding periods of 1 to 12 months, and it is unrelated to existing currency investment strategies, including risk-based currency momentum. The results hold for forecast horizons of 3, 12, and 24 months, and they are robust after accounting for transaction costs. The idiosyncratic component of currency expectations does not contain important information for the cross-section of currency returns. Our strategy is more significant for currencies with low sentiment and it is not driven by volatility and illiquidity. The results are robust when we extract the systematic component of the forecasts using a larger number of predictors.

We apply various test portfolios and alternative statistical methodologies to evaluate the performance of eleven prominent asset pricing models. To compile the test portfolios, we construct 105 anomalies in China and apply the 23 significant anomalies as test assets for model comparison. The results indicate that in the time-series test and anomalies explanation, the Hou et al. (2019) five-factor q model exhibits the best overall performance. The pairwise cross-sectional R^2s and the multiple model comparison tests affirm that the Hou et al. (2019) five-factor q model, the Fama and French (2018) six-factor (FF6) model and the Kelly et al. (2019) five-factor Instrumented Principal Component Analysis (IPCA5) model stand out as the top performers. Notably, the performance of the five-factor q model is insensitive to variations in experimental design.

We utilize ridge regression to create a novel set of characteristics-based "ridge factors". We propose Bayesian Average Stochastic Discount Factors (SDFs) based on these ridge factors, addressing model uncertainty in line with asset pricing theory. This approach shrinks the relative contribution of low-variance principal portfolios, avoiding model selection and presumption of a "true model". Our results demonstrate that ridge factor principal portfolios can achieve greater sparsity while maintaining prediction accuracy. Additionally, our Bayesian average SDF produces a higher Sharpe ratio for the tangency portfolio compared to other models.