Algorithmic trading and intra-industry information transfer

• 成果类型: Article
• 署名作者: Zhang, Xiaori; Jiang, Christine; Young, Danqing
• 署名单位: Guangdong University of Technology; Fudan University; Chinese University of Hong Kong
• 刊物名称: REVIEW OF ACCOUNTING STUDIES
• ISSN/ISSBN: 1380-6653; 1573-7136
• DOI: 10.1007/s11142-026-09954-3
• 发表日期: 2026-06
• 页码: 745-785
• 关键词: Algorithmic trading; Information transfer; Earnings announcement; Industry-related information; G14; M41; D53; earnings announcements; stock-prices; frequency; investor; ANALYST

摘要

We examine the role of algorithmic trading in transmitting intra-industry information. Using a comprehensive U.S. sample, we find that algorithmic trading amplifies the stock price reactions of non-announcing firms to the earnings announcements of industry peers that report earlier in the same fiscal quarter. Further analyses reveal that sector exchange-traded funds serve as an important channel through which algorithmic trading facilitates the diffusion of industry information. Moreover, the effect of algorithmic trading strengthens when peers' information is more relevant to the focal firm and of higher reporting quality. Finally, our evidence suggests that these effects reflect enhanced price discovery rather than temporary overreaction. Overall, our findings illuminate the informational role of algorithmic trading and its implications for market efficiency.