This study highlights asymmetries in liquidity risk pricing from the perspective of heterogeneously informed traders facing changing levels of preference uncertainty. We hypothesize that higher illiquidity premium and liquidity risk betas may arise simultaneously in circumstances where investors are asymmetrically informed about their trading counterparts’ preferences and their financial firms’ timely valuations of assets . We first test the time-varying state transition patterns of IML, a traded liquidity factor of the return premium on illiquid-minus-liquid stocks, using a Markov regime-switching framework. We then investigate how the conditional price of the systematic risk of the IML fluctuate over time subject to changing levels of preference uncertainty. Empirical results from the Chinese stock market support our hypotheses that investors’ sensitivity to the IML systematic risk conditionally increase in times of higher preference uncertainty as proxied by the stock turnover and order imbalance. Further policy impact analyses suggest that China’s market liberalization efforts, contingent upon its recent stock connect and margin trading programs, reduce the conditional price of liquidity risk for affected stocks by helping the incorporation of information into stock prices more efficiently. Tighter macroeconomic funding conditions, on the contrary, conditionally increase the price of liquidity that investors require.

This paper investigates whether Environmental, Social, and Governance (ESG) performance influences the stock idiosyncratic risk and extreme risk. We find that the ESG performance of listed companies significantly reduces the stock idiosyncratic risk and extreme risk. Furthermore, we identify that this mitigating effect is shaped by the nature of enterprise ownership and the firm life cycle. Through additional mechanistic analysis, we confirm that ESG performance affects the stock price volatility risk of listed companies by reducing levels of corporate earnings management and bolstering corporate reputation, thereby alleviating both idiosyncratic risk and extreme risk in stock prices.

We show that the personal traits of analysts, as revealed by their political donations, influence their forecasting behavior and stock prices. Analysts who contribute primarily to the Republican Party adopt a more conservative fore- casting style. Their earnings forecast revisions are less likely to deviate from the forecasts of other analysts and are less likely to be bold. Their stock recommen- dations also contain more modest upgrades and downgrades. Overall, these analysts produce better quality research, which is recognized and rewarded by their employers, institutional investors, and the media. Stock market participants, how- ever, do not fully recognize their superior ability as the market reaction following revisions by these analysts is weaker.

Using data from 11 major international markets that celebrate six cultural New Year holidays that do not occur on January 1, we find that stock markets tend to outperform in days surrounding a cultural New Year. After controlling for firm characteristics, an average stock earns 2.5% higher abnormal returns across all markets in the month of a cultural New Year relative to other months of the year. Further evidence suggests that positive holiday moods, in conjunction with cash infusions prior to a cultural New Year, produce elevated stock prices, particularly among those stocks most preferred and traded by individual investors.

Corporate site visits provide investors with opportunities to obtain non-standard, tailored "soft" information about the firm. In this study, we investigate the impact of information disclosed from corporate site visits on stock market stability from the perspective of stock return volatility. Our findings suggest that it is the information disclosed rather than the visits themselves that significantly reduce stock return volatility, primarily by mitigating information asymmetry. Moreover, we observe that the volatility-mitigating effect of site visits is more pronounced when the visit information better aligns with investors' concerns and when it is more effectively disseminated. Our study contributes to the literature by demonstrating that the timely disclosure of site visit details serves as a stabilizing mechanism for stock prices through effective information mining and dissemination.

We examine whether large language models (LLMs) can extract contextualized representation of Chinese public news articles to predict stock returns. Based on representativeness and influences, we consider seven LLMs: BERT, RoBERTa, FinBERT, Baichuan, ChatGLM, InternLM, and their ensemble model. We show that news tones and return forecasts extracted by LLMs from Chinese news significantly predict future returns. The value-weighted long-minus-short portfolios yield annualized returns between 35% and 67%, depending on the model. Building on the return predictive power of LLM signals, we further investigate its implications for information efficiency. The LLM signals contain firm fundamental information, and it takes two days for LLM signals to be incorporated into stock prices. The predictive power of the LLM signals is stronger for firms with more information frictions, more retail holdings and for more complex news. Interestingly, many investors trade in opposite directions of LLM signals upon news releases, and can benefit from the LLM signals. These findings suggest LLMs can be helpful in processing public news, and thus contribute to overall market efficiency.

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.

This paper examines the effects of superstitious psychology on investors’ decision making in the context of Mercury retrograde, a special astronomical phenomenon meaning “everything going wrong”. Using natural experiments in the Chinese stock market, we find a significant decline in stock prices, approximately -3.14% in the vicinity of Mercury retrogrades, with a subsequent reversal following these periods. The Mercury effect is robust after considering seasonality, the calendar effect, and well-known firm-level characteristics. Our mechanism tests are consistent with model-implied conjectures that stocks covered by higher investor attention are more influenced by superstitious psychology in the extensive and intensive channels. A superstitious hedge strategy motivated by our findings can generate an average annualized market-adjusted return of 8.73%.

We use the event study method to assess the impact of China's National Centralized Drug Procurement (NCDP) policy on the stock price of A-share listed companies in pharmaceutical industry. And the empirical evidence reveals that the policy has a negative effect on the share prices of firms won the bids in the past six centralized procurement. The stock prices of winning bidders were more negatively affected than those of non-winning bidders. If the winning bid price continues to be depressed, we cannot rule out the possibility of a collective abandonment of bidding by quality manufacturers.

Factoring financing is the most widely used form of supply chain finance, which has been adopted by more and more enterprises. The existing literature focuses on the motivation of suppliers to adopt factoring financing and the factors that affect the development of factoring. However, little attention is paid to the results of factoring. This study uses the event study method, draws on the Extended Resource based theory (ERBT), discussing how the factoring business announcement affects the stock market value of listed companies from the perspective of competitive advantage and the firm's own characteristics. By manually collecting 205 factoring business announcements from 115 Chinese listed companies from October 2019 to December 2022, we found that: (1) from the perspective of competitive advantage, the announcement of factoring business by non-Combination of Industry and Finance enterprises or their holding enterprises has more positive impact on the stock price of the enterprises. There is no obvious relationship between the size of factoring quota and stock price. (2) From the perspective of the enterprise's own characteristics, the announcement of factoring business by state-owned enterprises and small-scale enterprises can have a positive impact on the stock price of the enterprise. Before and after the Civil Code came into effect, there was no significant difference in the relationship between factoring business announcements and stock prices. This study uses secondary data to fill the gap in the study of the impact of factoring announcements on stock market value. This paper discusses the relationship between factoring business announcement and stock market value from the perspective of competitive advantage for the first time, providing theoretical guidance for managers to adopt factoring business under what circumstances. In addition, this study also provides documentation for the empirical study of factoring business announcements in China.