盈利能力指数
收益
代理(统计)
交易策略
算法交易
业务
另类交易系统
信息不对称
内幕交易
金融经济学
电子交易
货币经济学
经济
金融市场
零售业
不平等
信息处理
财务
产业组织
结对贸易
库存(枪支)
股票交易
金融市场参与者
软件部署
公共信息
过程(计算)
金融服务
作者
ANNE YANRU CHANG,XI DONG,Xiumin Martin,Changyun Zhou
标识
DOI:10.1111/1475-679x.70063
摘要
ABSTRACT We are among the first to investigate how Generative AI (GenAI) shapes investors' trading activities. Using an AI‐sentiment measure extracted from earnings‐call transcripts to proxy for textual signals, we find notable shifts in trading behaviors around earnings calls. Before the wide deployment of ChatGPT, short selling was aligned with AI‐sentiment, whereas retail trading was not. However, following ChatGPT's deployment, the alignment of retail traders with AI‐sentiment significantly increases, while the alignment of short sellers weakens, albeit insignificantly. Stocks with higher information processing costs exhibit a more pronounced increase in retail trading alignment, scenarios where retail investors are likely to benefit more from AI. Using retail‐AI alignment as a proxy for the extent to which retail investors trade based on AI signals, we show that information asymmetry declines and retail investors' trading profitability improves, whereas short sale profitability declines in high retail‐AI alignment stocks. Exogenous outages reduce the alignment between retail trading and AI‐sentiment, allowing us to draw causal inferences. Collectively, this study suggests that AI is a promising technology for narrowing the information gap in the trading of complex textual financial disclosures between investor classes with clear disparities in the ability to process public disclosures.
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