This study investigates the role of contextual cues in memory-based decision-making within high-stakes trading environments. Using trade records from a large Chinese brokerage firm, we provide evidence that both extreme events (COVID-19 quarantines) and everyday contexts (geographic locations) trigger the recall of previously traded stocks, increasing the likelihood of subsequent orders for those stocks. The observed patterns align more closely with similarity-based recall than with alternative channels. Welfare analysis reveals that these memory-induced trades lead to substantial losses for the representative investor's portfolio. We also find evidence at the market level: when the geographical distribution of quarantine risks is recalled, the probability of recalling the cross-sectional stock return-volume distribution from the same day increases by 1.6 percentage points. This study provides evidence from a real-world setting for memory-based theories, particularly similarity-based recall, and highlights a novel channel through which contextual cues affect financial markets.

Mutual funds create liquidity for investors by issuing demandable equity shares while holding illiquid securities. We study the implications of this liquidity creation by examining frequent trading suspensions in China, which temporarily eliminate market liquidity in affected stocks. These suspensions cause significant mispricing of mutual funds due to inaccurate valuations of their illiquid holdings. We find that investors actively acquire information about suspended stocks held by mutual funds, driving flows into underpriced funds. This information is subsequently incorporated into stock prices when trading resumes. Our findings suggest that mutual fund liquidity creation stimulates information acquisition about illiquid, information-sensitive assets.

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.

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.

We investigate the information cost of stock trading during the 2000 presidential election. We find that the uncertainty of the election induces information asymmetry of politically sensitive firms under the Bush/Gore platforms. The unusual delay in election results in a significant increase in the adverse selection component of trading cost of politically sensitive stocks. Cross-sectional variations in bid-ask spreads are significantly and positively related to changes in information cost, controlling for the effects of liquidity cost and stock characteristics. This empirical evidence is robust to different estimation methods.

Building upon the seminal work of Easley, Kiefer, O’Hara and Paperman (1996), we develop a framework to investigate the relationship between the behavior of uninformed investors and the time-varying informed trading activities. We allow the arrival rates for uninformed traders to follow a Markov switching process where the transition probabilities depend on market fundamentals. Informed traders may match the level of the uninformed arrival rate with certain probability so as to make better use of the camouflage provided by the uninformed transactions. Our empirical estimation of NYSE stocks shows that the uninformed transition probabilities are indeed time-varying, so is the probability of information content. The estimated probability of information content predicts the opening, median and closing spreads. There is evidence that uninformed investors exhibit momentum chasing and “noise herding” behavior. There is also a positive “market spillover” effect in the uninformed trading activities. We find that the “clustering” of trading activities by uninformed and informed traders seem to be more likely on low volume days, and the uninformed trading activities are responsible for most of the stock trading volatilities.