The Impact of Negative Public Sentiment on Stock Price Volatility: A Case Study of Qiaqia Food

Abstract

In the digital economy era, the deep integration of digital technologies and social media has enabled negative public sentiment to break through spatiotemporal constraints, with its dissemination speed and impact scope expanding exponentially. Its diffusion intensifies market information asymmetry, triggers short-term violent fluctuations in stock prices, and has become a critical risk variable affecting the stable operation of the capital market. Previous traditional studies have mostly relied on linear assumptions to investigate the relationship between negative public sentiment and stock prices, failing to fully reveal the complex dynamics potentially induced by investors’ irrational behavior. To address this gap, this study takes Qiaqia Food Co., Ltd., a representative enterprise in China’s food industry, as the research object. Through manually collected data and empirical analysis methods, it innovatively constructs a quadratic polynomial regression model to deeply explore the nonlinear mechanism by which negative public sentiment affects stock price volatility and to empirically examine the moderating role of media authority attributes. The following conclusions are drawn: there exists a significant inverted U-shaped relationship between the intensity of public sentiment and cumulative abnormal returns (CAR). Moreover, after controlling for sentiment intensity, reports from authoritative media can effectively buffer market panic. The theoretical contributions of this study are reflected at two levels. First, by constructing a quadratic polynomial model, it breaks through the previous analytical paradigm that relied on linear relationships, providing a basis for quantifying the dynamic changes in the impact of public sentiment. Second, it analyzes the moderating effect of media authority attributes, laying a solid foundation for subsequent in-depth research.