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Price revelation from insider trading: Evidence from hacked earnings news

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  • Akey, Pat
  • Grégoire, Vincent
  • Martineau, Charles

Abstract

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.

Suggested Citation

  • Akey, Pat & Grégoire, Vincent & Martineau, Charles, 2022. "Price revelation from insider trading: Evidence from hacked earnings news," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1162-1184.
    • Handle: RePEc:eee:jfinec:v:143:y:2022:i:3:p:1162-1184
    DOI: 10.1016/j.jfineco.2021.12.006
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    More about this item

    Keywords

    Cyber risks; Earnings announcements; Hard and soft information; Informed trading; Liquidity; Machine learning; Market microstructure; Price discovery;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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