This study, using two herding dynamics metrics and Glosten–Jagannathan–Runkle Generalized Autoregressive Conditional Heteroskedasticity (GJR-GARCH) model, forecasts market trends, captures asymmetric volatility, and reveals the generative AI (GenAI) ecosystem's impact on individual assets’ returns. Results of this study highlight distinctive traits of each GenAI equity, crucial for strategic positioning, especially for investors in tech stocks tied to GenAI. Herding behavior exhibits greater strength in the initial four months post-announcement of ChatGPT, gradually diminishing. GJR-GARCH reports that most of GenAI stocks do not exhibit statistically significant leverage effects. These findings provide valuable insights to navigate the dynamic landscape of GenAI investments.

中文翻译：

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在关键技术进步的背景下解读生成式人工智能投资中的羊群动态：时间线视角

这项研究使用两个羊群动态指标和 Glosten-Jagannathan-Runkle 广义自回归条件异方差 (GJR-GARCH) 模型，预测市场趋势，捕捉不对称波动性，并揭示生成式人工智能 (GenAI) 生态系统对单个资产回报的影响。这项研究的结果凸显了每只 GenAI 股票的独特特征，这对于战略定位至关重要，特别是对于与 GenAI 相关的科技股投资者而言。 ChatGPT 发布后的最初四个月内，羊群行为表现出较强的强度，随后逐渐减弱。 GJR-GARCH 报告称，大多数 GenAI 股票并未表现出统计上显着的杠杆效应。这些发现为驾驭 GenAI 投资的动态格局提供了宝贵的见解。