The rise of automated trading systems has made stock trading more accessible and convenient, reducing the link between traditional illiquidity measures and stock returns. However, empirical data in China’s stock market shows conflicting results. We find a significantly positive correlation between intraday illiquidity and future returns in China’s stock market. We offer that the pricing ability of this intraday illiquidity originates from the correlation between trading activity and intraday return. This finding provides compelling out-of-sample evidence for the debate regarding the pricing of the Amihud (2002) measure in the U.S. market. Additionally, we create an intradayreturn illiquidity factor that outperforms Liu, Stambaugh, and Yuan (2019) sentiment factors in China’s stock market.

Using a proprietary granular database of a major Chinese stock exchange, we examine heterogenous investors’ trading dynamics around one of the most important macro announcements of the Chinese central bank, the monthly release of monetary aggregates data. Exploiting the trading heterogeneity across assets and across investor types, we find that before announcements, institutional investors reduce their aggregate stock exposure while over-weighing riskier stocks of smaller caps, whereas retail investors provide liquidity by increasing their aggregate stock exposure and avoiding the riskier stocks. Large retail and institutional investors become more informed before announcements and trade in correct directions consistent with the news surprises after announcements, while smaller retail investors trade in opposite directions. While the institutional investors accumulate positive returns with risk compensated, the market realizes sizable pre-announcement equity premium.

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.

Using a proprietary granular database of a major Chinese stock exchange, we examine heterogenous investors’ trading dynamics around one of the most important macro announcements of the Chinese central bank, the monthly release of monetary aggregates data. Exploiting the trading heterogeneity across assets and across investor types, we find that before announcements, institutional investors reduce their aggregate stock exposure while over-weighing riskier stocks of smaller caps, whereas retail investors provide liquidity by increasing their aggregate stock exposure and avoiding the riskier stocks. Large retail and institutional investors become more informed before announcements and trade in correct directions consistent with the news surprises after announcements, while smaller retail investors trade in opposite directions. While the institutional investors accumulate positive returns with risk compensated, the market realizes sizable pre-announcement equity premium.

Using a proprietary database of stock transactions in China, we document significant trading disparities between retail and institutional investors around important macro announcements. These disparities are driven by differences in information positions. We find that before the monthly releases of China’s key monetary aggregates data, institutional investors reduce their stock exposure and shift towards riskier, smaller-cap stocks. In contrast, retail investors increase their stock exposure and avoid riskier stocks. The risk positions of institutional investors are compensated by the pre-announcement premium in smaller stocks. Following the announcements, institutional investors trade in line with news surprises, contributing to price discovery and reinforcing monetary policy transmission into asset prices. Our findings have implications for understanding announcement-related equity premium and for evaluating the general efficiency of stock market in China.

Salience theory has been proposed as a new stock trading strategy. Therefore, to assess the validity of this proposal, a complex decision trading system was constructed based on salience theory, a variational mode decomposition (VMD) model, a bidirectional gated recurrent unit (BiGRU) model, and high-frequency trading. The system selected 30 Chinese new energy concept stocks, ranked the stocks using salience theory, and selected the top and bottom three stocks for two portfolios. Twelve stages were established, after which the VMD and BiGRU models were applied to the predictions. The final predicted returns for the high ST group A (GA) were 194.06% and for the low ST group B (GB) were 165.88%. This paper validated the powerful utility of salience theory and deep learning to analyze Chinas new energy market. And it explains the issues and questions raised by previous researchers.

In this paper, using news reports and stock trading data from China, we document that stocks covered by the same media platform tend to comove together and refer to it as media-driven comovement. This finding remains significant both by conducting time series regressions of individual stock returns on co-coverage portfolio returns and by calculating the Pearson correlations among stocks that are co-covered by the same media platform. This is a novel type of comovement since it cannot be fully explained by common factors (e.g., additions to market indices) that lead to comovement but accords well with the investment habitat view. Besides, we find no statistically significant relationship between the frequency of co-coverage and the magnitude of comovement. To better illustrate the economic significance of this media-driven comovement, we construct a trading strategy which earns a monthly return of 115 basis point.

This paper studies the trading behavior of investors facing a large number of firm-initiated stock trading suspension events during the Chinese stock market crisis in July of 2015. Using account-level trading data from the Shanghai Stock Exchange, we find that investors with a higher fraction of holding value in suspension sell less (or purchase more) of non-suspended stocks. Consequently, non-suspended stocks whose shareholders having high average account- level suspension fraction experience a relative price appreciation, which subsequently reverses. These evidences indicate that trading suspension can calm down investors and therefore helps to stabilize the volatile market in crisis time.

This paper studies the trading behavior of investors facing a large number of firm-initiated stock trading suspension events during the Chinese stock market crisis in July of 2015. Using account-level trading data from the Shanghai Stock Exchange, we find that investors with a higher fraction of holding value in suspension sell less (or purchase more) of non-suspended stocks. Consequently, non-suspended stocks whose shareholders having high average account level suspension fraction experience a relative price appreciation, which subsequently reverses. These evidences indicate that trading suspension can calm down investors and therefore helps to stabilize the volatile market in crisis time.

Using data on stock trading and accounting information from 2000 to 2018, we construct 426 anomalies and propose the multiple hurdle of 2.85 in the Chinese A-share stock market. With single sort portfolio analysis on value-weighted returns, we find that 98 (27) anomalies have significant raw returns at the 5% level with absolute t-value larger than 1.96 (2.85). After risk adjustment using the Liu, Stambaugh and Yuan (2019) three-factor model, 16 (2) anomalies have significant alphas for single (multiple) tests, about half of which are based on liquidity information, while alphas for accounting anomalies are less significant. After regressing on the four-factor model with turnover, the liquidity anomalies become insignificant. We construct the composite anomalies, and find that the majority can pass the multiple test hurdle.