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Using High-Frequency Transaction Data to Estimate the Probability of Informed Trading

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  • Anthony Tay
  • Christopher Ting
  • Yiu Kuen Tse
  • Mitch Warachka

Abstract

This paper applies the asymmetric autoregressive conditional duration (AACD) model of Bauwens and Giot (2003) to estimate the probability of informed trading (PIN) using irregularly spaced transaction data. We model trade direction (buy versus sell orders) and the duration between trades jointly. Unlike the Easley, Hvidkjaer, and O'Hara (2002) approach, which uses the aggregate numbers of daily buy and sell orders to estimate PIN, our methodology allows for interactions between consecutive buy-sell orders and accounts for the duration between trades and the volume of trade. We extend the Easley--Hvidkjaer--O'Hara framework by allowing the probabilities of good news and bad news to vary each day. Our PIN estimates can be computed daily as well as over intraday intervals. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Suggested Citation

  • Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2009. "Using High-Frequency Transaction Data to Estimate the Probability of Informed Trading," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(3), pages 288-311, Summer.
  • Handle: RePEc:oup:jfinec:v:7:y:2009:i:3:p:288-311
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbp005
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    Citations

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    Cited by:

    1. Petchey, James & Wee, Marvin & Yang, Joey, 2016. "Pinning down an effective measure for probability of informed trading," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 456-475.
    2. Moonsoo Kang & Kiseok Nam, 2015. "Informed trade and idiosyncratic return variation," Review of Quantitative Finance and Accounting, Springer, vol. 44(3), pages 551-572, April.
    3. Agudelo, Diego A. & Giraldo, Santiago & Villarraga, Edwin, 2015. "Does PIN measure information? Informed trading effects on returns and liquidity in six emerging markets," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 149-161.
    4. Thomas Pöppe & Michael Aitken & Dirk Schiereck & Ingo Wiegand, 2016. "A PIN per day shows what news convey: the intraday probability of informed trading," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1187-1220, November.
    5. Degiannakis, Stavros & Filis, George, 2016. "Forecasting oil price realized volatility: A new approach," MPRA Paper 69105, University Library of Munich, Germany.
    6. Hahn, TeWhan & Ligon, James A. & Rhodes, Heather, 2013. "Liquidity and initial public offering underpricing," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4973-4988.

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