Algorithmic trading and intra-industry information transfer
研究算法交易如何放大行业内信息传递，发现其通过行业ETF渠道增强非公告公司对同行盈余公告的股价反应，且该效应在信息相关性高、报告质量好时更强，反映价格发现而非过度反应。
Abstract 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.