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High-Frequency Informed Trading Signals Around Corporate Announcements

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Summary

The document summarizes research using high-frequency trading data to estimate daily conditional probabilities of informed buying and selling, extending the probability-of-informed-trading approach. It applies these measures around merger announcements and earnings releases, where private information or skilled interpretation may affect trading before and after the news. The summary reports that informed activity ahead of announcements can reveal information leakage and cause prices to move before the public event, reducing the announcement-period return response.

For mergers, it describes associations between informed trading and outcomes such as deal withdrawal or the emergence of competing bidders. Around earnings announcements, it reports informed trading in the days beforehand, with activity related to the size of earnings surprises; post-announcement informed buying is associated with subsequent stock returns. These are findings summarized from overseas historical research, not a trading system or proof that the signals remain profitable after costs. The document provides no detailed model specification, sample construction, or numerical effect sizes, so the evidence and its generalizability cannot be assessed from this summary alone.

Key ideas

  • A high-frequency measure estimates daily conditional probabilities of informed buying and selling.
  • Trading before merger announcements may reflect leaked information and can reduce the market’s reaction on announcement day.
  • Informed trading around mergers is associated with deal outcomes, including withdrawals and competing bids.
  • Informed activity before earnings releases is related to earnings surprises, while post-release buying is associated with later returns.
  • The reported findings summarize historical overseas research and do not establish a directly tradable or broadly generalizable strategy.

Tags

EquitiesHigh-frequency tradingEvent-drivenMarket microstructureStatistics

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.