The Effect of Algorithmic Trading on Management Guidance
研究发现算法交易活动增加时，管理层会提高盈余公告时指引的数量和质量，以弥补价格信息含量下降，从而降低信息不对称。
ABSTRACT I investigate whether algorithmic trading (AT) affects the provision of management guidance. Existing research finds that AT decreases fundamental information acquisition before earnings announcements and consequently reduces the informativeness of prices. To compensate for reduced information acquisition, I predict and find that managers at firms with more AT activity increase the quantity and quality of guidance issued at earnings announcements. Evidence is consistent with managers responding to reduced information acquisition, as opposed to changes in liquidity, and results suggest guidance in response to AT is effective at reducing information asymmetry. These findings identify a new channel through which AT affects stock price informativeness by documenting a link to managers’ disclosure decisions. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G14; G19; G10.