Abstract
We utilized a Python program to collect analysts’ reports on the constituents of the CSI 300 (China Securities Index). From these reports, we extracted analyst ratings, readability, and visualization using text analysis techniques. Additionally, a FinBERT model was employed to evaluate the tone and disagreement among analyst reports. Subsequently, the FGLS model was developed to explore the influence of analysts’ reports on stock liquidity. The analysis revealed a positive impact of analyst ratings on stock liquidity, with all qualitative indicators playing significant moderating roles. Specifically, there was a more pronounced response in stock liquidity to ratings when accompanied by higher readability, richer visualization, a more positive tone in the report, and lower disagreement. Our study highlights that investors consider both ratings and qualitative information from analyst reports, with the latter guiding investors on how to interpret ratings effectively. These findings have implications for investors, analysts, and regulators.
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