Price revelation from insider trading: Evidence from hacked earnings news
Vincent Grégoire and
Journal of Financial Economics, 2022, vol. 143, issue 3, 1162-1184
From 2010 to 2015, a group of traders illegally accessed earnings information before their public release by hacking several newswire services. We use this scheme as a natural experiment to investigate how informed investors select among private signals and how efficiently financial markets incorporate private information contained in trades into prices. We construct a measure of qualitative information using machine learning and find that the hackers traded on both qualitative and quantitative signals. The hackers’ trading caused 15% more of the earnings news to be incorporated in prices before their public release. Liquidity providers responded to the hackers’ trades by widening spreads.
Keywords: Cyber risks; Earnings announcements; Hard and soft information; Informed trading; Liquidity; Machine learning; Market microstructure; Price discovery (search for similar items in EconPapers)
JEL-codes: G10 G12 G14 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:143:y:2022:i:3:p:1162-1184
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