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.

The asymmetric dissemination of information among financial firms in the financial market reflects their asymmetric response to the dissemination of both positive and negative information. However, it is worth studying whether this asymmetry will intensify or alleviate under different financial market conditions. Based on high-frequency minute stock price data of Chinese A-share listed financial firms from July 2020 to July 2023, we decompose the good and bad information, as well as the positive and negative volatility information in the return series. We utilize the quantile cross-spectral correlation method to construct an information overflow network at monthly intervals. We use the MVMQ-CAViaR model to estimate the value at risk (VaR) for various quantiles and build a risk spillover network that incorporates both positive and negative tail risk information, using the quantile dynamic SIM-COVAR-TENET model. We calculated the network dissemination efficiency of both good and bad information, including average speed, speed deviation, densest speed, and depth, to explore the changes in the asymmetry of good and bad information dissemination under different financial market conditions. We get that when the financial market is booming, financial firms’ asymmetric response to good and bad information will increase, and the firms will pay more attention to bad information. When the financial market declines, the asymmetric response of financial firms to good and bad information is diminished, and their sensitivity to both positive and negative information is heightened. In addition, the dissemination of bad information by firms in the five sub-financial industries across various markets exacerbates the asymmetric response of other financial firms to good and bad information. More importantly, the release of positive return information, negative volatility information, and highly negative tail risk information by the real estate financial firms all impact the asymmetric response of financial firms to good and bad information in a prosperous financial market. In recessionary financial markets, financial regulators can strategically release positive information to mitigate the decline in the financial market. Conversely, in a booming financial market, financial regulators should be cautious of the negative impact that bad information can have on financial firms, particularly in relation to the excessive growth of the real estate sector and the potential chain reaction of significant adverse events.

The asymmetric dissemination of information among financial firms in the financial market reflects their asymmetric response to the dissemination of both positive and negative information. However, it is worth studying whether this asymmetry will intensify or alleviate under different financial market conditions. Based on high-frequency minute stock price data of Chinese A-share listed financial firms from July 2020 to July 2023, we decompose the good and bad information, as well as the positive and negative volatility information in the return series. We utilize the quantile cross-spectral correlation method to construct an information overflow network at monthly intervals. We use the MVMQ-CAViaR model to estimate the value at risk (VaR) for various quantiles and build a risk spillover network that incorporates both positive and negative tail risk information, using the quantile dynamic SIM-COVAR-TENET model. We calculated the network dissemination efficiency of both good and bad information, including average speed, speed deviation, densest speed, and depth, to explore the changes in the asymmetry of good and bad information dissemination under different financial market conditions. We get that when the financial market is booming, financial firms’ asymmetric response to good and bad information will increase, and the firms will pay more attention to bad information. When the financial market declines, the asymmetric response of financial firms to good and bad information is diminished, and their sensitivity to both positive and negative information is heightened. In addition, the dissemination of bad information by firms in the five sub-financial industries across various markets exacerbates the asymmetric response of other financial firms to good and bad information. More importantly, the release of positive return information, negative volatility information, and highly negative tail risk information by the real estate financial firms all impact the asymmetric response of financial firms to good and bad information in a prosperous financial market. In recessionary financial markets, financial regulators can strategically release positive information to mitigate the decline in the financial market. Conversely, in a booming financial market, financial regulators should be cautious of the negative impact that bad information can have on financial firms, particularly in relation to the excessive growth of the real estate sector and the potential chain reaction of significant adverse events.