Does generative AI facilitate investor Trading? Early evidence from ChatGPT outages

• 成果类型: Article
• 署名作者: Cheng, Qiang; Lin, Pengkai; Zhao, Yue
• 署名单位: Singapore Management University
• 刊物名称: JOURNAL OF ACCOUNTING & ECONOMICS
• ISSN/ISSBN: 0165-4101; 1879-1980
• DOI: 10.1016/j.jacceco.2025.101821
• 发表日期: 2025
• 页码: 101821
• 关键词: generative AI; ChatGPT; trading volume; information asymmetry; Price informativeness; institutional investors; INFORMATION; MARKET; underreaction; attention; news

摘要

In this paper, we use ChatGPT outages to provide early evidence on whether investors rely on generative artificial intelligence (GenAI) to perform professional tasks and the associated impact on stock price informativeness. We document a significant decline in stock trading volume during ChatGPT outages. The effect is stronger for firms with corporate news released immediately before or during the outages and for firms with higher ownership held by transient institutional investors. We then document declines in short-run price impact and return variance during the outage periods, consistent with reduced informed trading. Lastly, we document a positive effect of GenAI-assisted trading on long-run stock price informativeness. Overall, our findings indicate that a significant number of investors use ChatGPT in ways that influence their trading decisions and market outcomes. Future research can investigate the mechanisms underlying these GenAI effects and the potential risks of using GenAI for trading.