Unit Root Test.

The literature implies an increased interest in AI-based companies, but it is unclear how investor attention affects their volatility. This study fills the gap by investigating the relationship between investor attention, as measured by Google Trends data, and the volatility of AI-based stocks. Using weekly adjusted closing stock price data for 8 AI-based stocks from 2015 to 2024, quantile regression analysis was used to identify the impact of investor attention at various volatility levels. Though the direction of the effect differs, the data shows that investor attention has a considerable impact on the volatility of AI-based companies. Although most stocks show a positive relationship, Tencent Holding’s unique traits or market dynamics impact its response to investor attention. The study uses GARCH and ARIMA models to investigate stock volatility dynamics across time. The findings of this study show that market information changes are critical in driving volatility variations. This study provides insights into the intricate relationship between investor attention and market volatility, with substantial implications for investors and policymakers. Understanding these processes can help investors make educated decisions and allocate resources more effectively, while regulators can devise policies to reduce possible risks and promote market stability.

现有文献表明，学界与业界对人工智能（AI）企业的关注度日益提升，但目前尚不明确投资者关注度如何影响此类企业的股价波动。本研究通过以谷歌趋势（Google Trends）数据作为投资者关注度的衡量指标，探究AI相关个股的股价波动与投资者关注度之间的关联，以此填补这一研究空白。本研究采集了2015年至2024年间8只AI相关个股的周度调整收盘价数据，采用分位数回归分析，以识别不同波动水平下投资者关注度的影响效应。尽管影响方向存在差异，但数据结果表明，投资者关注度对AI企业的股价波动具有显著影响。尽管多数个股的股价波动与投资者关注度呈正相关关系，但腾讯控股（Tencent Holding）因其独特的企业特质与市场运行逻辑，其对投资者关注度的响应模式有所不同。本研究同时采用广义自回归条件异方差（GARCH）模型与自回归整合移动平均（ARIMA）模型，探究股价波动的时变动态特征。本研究结果显示，市场信息的变动是驱动股价波动变化的核心因素。本研究揭示了投资者关注度与市场波动之间的复杂关联，可为投资者与政策制定者带来重要启示。厘清上述作用机制，有助于投资者做出更具依据的投资决策并更高效地配置资源，同时监管机构也可据此制定政策以降低潜在风险、维护市场稳定。