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.

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.

One commonly adopted practice in classifying retail and institutional orders is based on order size. Due to the increasing use of small orders by institutional investors, size-based classification can lead to an error rate over 20%. To improve the accuracy of the order size algorithm, we study the order patterns and uncover a higher tendency of retail investors trading in multiples of 500 shares. We modify the original order size algorithm by incorporating the feature of share roundedness. The modified algorithm substantially improves the accuracy of identifying retail and institutional investors in China. Order imbalances derived from the modified algorithm better predict future stock returns.

We examine the financial and real implications of bank CEOs’ social minds induced by female socialization on sustainable loans. We find evidence of an economically sizable and statistically significant bank CEO-daughter effect in lending behaviours, controlling for borrower industry as well as bank characteristics. In specific, the “greenness” of a bank is significantly higher, when the lead bank CEO parents a first-born daughter compared to an otherwise lender. Looking at the specific lending contracts written by banks, we find that lead banks whose CEOs parent a first-born daughter provide loans with lower spread, fewer financial covenants, and less likely to require collateral, for borrowers with better Corporate Social Responsibility (CSR) performance. Furthermore, we find that bank CEOs’ parenting experience with first-born daughters would predict borrowing firms’ future CSR performance positively, suggesting banks with CEOs raising a first-born daughter would promote the corporate social activities of borrowers.

This study explores the role of sentiment in predicting future stock return volatility in the Chinese A-share market. Specifically, we conduct a composite sentiment index capturing both investor and manager sentiment. The former is measured by overnight returns, and the latter is measured by a textual tone based on the information in the Management Discussion and Analysis section of the annual reports. Empirically, we find that the composite index is positively associated with subsequent stock realized volatility and the result remains robust after controlling for a set of firm characteristics and state ownership. Besides, the result also shows that investor attention can help dissect the sentiment—volatility relation.

This paper presents an innovative Comprehensive Growth Dynamic Model (CGDM). CGDM is designed to simulate the temporal evolution of an event, incorporating economic and social factors. CGDM is a regression of logistic regression, power law regression, and Gaussian perturbation term. CGDM is comprised of logistic regression, power law regression, and Gaussian perturbation term. CGDM can effectively forecast the temporal evolution of an event, incorporating economic and social factors. The illicit trade in wildlife has a deleterious impact on the ecological environment. In this paper, we employ CGDM to forecast the trajectory of illegal wildlife trade from 2024 to 2034 in China. The mean square error is utilized as the loss function. The model illuminates the future trajectory of illegal wildlife trade, with a minimum point occurring in 2027 and a maximum point occurring in 2029. The stability of contemporary society can be inferred. CGDM's robust and generalizable nature is also evident.

This paper studies the transmission of monetary policy to the stock market through investors’ discount factors. To isolate this channel, we investigate the effect of US monetary policy surprises on the ratio of prices of the same stock listed simultaneously in Hong Kong and Mainland China, and thereby control for revisions in cash-flow expectations. We find this channel to be strong and asymmetric, with the effect driven by surprise monetary policy interest rate cuts. A 100 basis point surprise cut results in a 30 basis point increase in the ratio of stock prices over 5 days. These results suggest significant slow-moving reductions in stock market risk premia following accommodating monetary policy surprises.