Ravichandran Sweena, Afjal Mohd
VIT Business School, Vellore Institute of Technology, Vellore, India.
PLoS One. 2025 May 28;20(5):e0324450. doi: 10.1371/journal.pone.0324450. eCollection 2025.
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.
文献表明对人工智能相关公司的兴趣有所增加，但尚不清楚投资者关注如何影响其波动性。本研究通过调查以谷歌趋势数据衡量的投资者关注与人工智能相关股票的波动性之间的关系来填补这一空白。利用2015年至2024年8只人工智能相关股票的每周调整后收盘价数据，采用分位数回归分析来确定投资者关注在不同波动水平下的影响。尽管影响方向不同，但数据表明投资者关注对人工智能相关公司的波动性有相当大的影响。虽然大多数股票呈现正相关关系，但腾讯控股的独特特征或市场动态影响了其对投资者关注的反应。该研究使用GARCH和ARIMA模型来研究股票波动性随时间的动态变化。本研究结果表明，市场信息变化对推动波动性变化至关重要。本研究深入探讨了投资者关注与市场波动性之间的复杂关系，对投资者和政策制定者具有重大意义。了解这些过程有助于投资者做出明智决策并更有效地分配资源，而监管机构可以制定政策以降低潜在风险并促进市场稳定。
