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High Frequency Trading, Information, and Takeovers

  • M. Humphery-Jenner

Research output: Working paperDiscussion paperOther research output

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Abstract

This paper (1) proposes new variables to detect informed high-frequency trading (HFT), (2) shows that HFT can help to predict takeover targets, and (3) shows that HFT in uences target announcement announcement returns. Prior literature suggests that informed trade may occur before takeovers, but has not examined the role of HFT and has relied on monthly measures of informed trade (such as PIN or the spread components). I propose microstructure-based variables to detect HFT that are derived from hazard modeling and from VWAP trading algorithms. I show that these can help predict takeover targets and are significantly related to target announcement returns. This highlights the existence of pre-takeover informed trade and the need to control for it when analyzing takeover returns.
Original languageEnglish
Place of PublicationTilburg
PublisherEconomics
Volume2011-011
Publication statusPublished - 2011

Publication series

NameEBC Discussion Paper
Volume2011-011

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Keywords

  • High Frequency Trading
  • Takeovers
  • Algorithmic Trading

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