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What does PIN identify? Evidence from the T-bill market

Author

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  • Akay, Ozgur (Ozzy)
  • Cyree, Ken B.
  • Griffiths, Mark D.
  • Winters, Drew B.

Abstract

The probability of informed trading (PIN) measure has been increasingly used in empirical research in finance. However, there is a growing debate as to whether PIN measures information-based or liquidity-based trading. We contribute to the discussion by estimating PIN using transaction data for one-month T-bills. Our PIN estimates exceed those reported for equities, despite it being unlikely that the probability of informed trading is higher in T-bills than equities. We conclude that PIN identifies trading clusters and that the source of the clustering depends on the economics of the market. The economics of the T-bill market suggest discretionary liquidity traders are the likely source of the clustering.

Suggested Citation

  • Akay, Ozgur (Ozzy) & Cyree, Ken B. & Griffiths, Mark D. & Winters, Drew B., 2012. "What does PIN identify? Evidence from the T-bill market," Journal of Financial Markets, Elsevier, vol. 15(1), pages 29-46.
    • Handle: RePEc:eee:finmar:v:15:y:2012:i:1:p:29-46
    DOI: 10.1016/j.finmar.2011.08.005
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    as
    1. Martin D.D. Evans & Richard K. Lyons, 2017. "Order Flow and Exchange Rate Dynamics," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 6, pages 247-290, World Scientific Publishing Co. Pte. Ltd..
    2. Harvey, Campbell R. & Huang, Roger D., 2002. "The impact of the Federal Reserve Bank's open market operations," Journal of Financial Markets, Elsevier, vol. 5(2), pages 223-257, April.
    3. Fleming, Michael J, 2002. "Are Larger Treasury Issues More Liquid? Evidence from Bill Reopenings," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(3), pages 707-735, August.
    4. Duarte, Jefferson & Young, Lance, 2009. "Why is PIN priced?," Journal of Financial Economics, Elsevier, vol. 91(2), pages 119-138, February.
    5. David Easley & Soeren Hvidkjaer & Maureen O'Hara, 2002. "Is Information Risk a Determinant of Asset Returns?," Journal of Finance, American Finance Association, vol. 57(5), pages 2185-2221, October.
    6. Michael J. Fleming, 2003. "Measuring treasury market liquidity," Economic Policy Review, Federal Reserve Bank of New York, issue Sep, pages 83-108.
    7. Glosten, Lawrence R. & Harris, Lawrence E., 1988. "Estimating the components of the bid/ask spread," Journal of Financial Economics, Elsevier, vol. 21(1), pages 123-142, May.
    8. Craig H Furfine & Eli M Remolona, 2002. "What's behind the liquidity spread? On-the-run and off-the-run US Treasuries in autumn 1998," BIS Quarterly Review, Bank for International Settlements, June.
    9. Boni, Leslie & Leach, Chris, 2004. "Expandable limit order markets," Journal of Financial Markets, Elsevier, vol. 7(2), pages 145-185, February.
    10. Boehmer, Ekkehart & Grammig, Joachim & Theissen, Erik, 2007. "Estimating the probability of informed trading--does trade misclassification matter?," Journal of Financial Markets, Elsevier, vol. 10(1), pages 26-47, February.
    11. Michael J. Barclay & Terrence Hendershott & Kenneth Kotz, 2006. "Automation versus Intermediation: Evidence from Treasuries Going Off the Run," Journal of Finance, American Finance Association, vol. 61(5), pages 2395-2414, October.
    12. Joel Hasbrouck, 1999. "The Dynamics of Discrete Bid and Ask Quotes," Journal of Finance, American Finance Association, vol. 54(6), pages 2109-2142, December.
    13. Easley, David & Hvidkjaer, Soeren & O’Hara, Maureen, 2010. "Factoring Information into Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 293-309, April.
    14. Aktas, Nihat & de Bodt, Eric & Declerck, Fany & Van Oppens, Herve, 2007. "The PIN anomaly around M&A announcements," Journal of Financial Markets, Elsevier, vol. 10(2), pages 169-191, May.
    15. Easley, David & Kiefer, Nicholas M & O'Hara, Maureen, 1997. "One Day in the Life of a Very Common Stock," The Review of Financial Studies, Society for Financial Studies, vol. 10(3), pages 805-835.
    16. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    17. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    18. Kenneth D. Garbade, 2008. "Why the U.S. Treasury began auctioning Treasury bills in 1929," Economic Policy Review, Federal Reserve Bank of New York, vol. 14(Jul), pages 31-47.
    19. Leslie Boni & J. Chris Leach, 2002. "Supply contraction and trading protocol: an examination of recent changes in the U.S. Treasury market," Proceedings, Federal Reserve Bank of Cleveland, pages 740-766.
    20. Griffiths, Mark D. & Lindley, James T. & Winters, Drew B., 2010. "Market-making costs in Treasury bills: A benchmark for the cost of liquidity," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2146-2157, September.
    21. Haitao Li & Junbo Wang & Chunchi Wu & Yan He, 2009. "Are Liquidity and Information Risks Priced in the Treasury Bond Market?," Journal of Finance, American Finance Association, vol. 64(1), pages 467-503, February.
    22. repec:bla:jfinan:v:59:y:2004:i:6:p:2623-2654 is not listed on IDEAS
    23. Michael J. Fleming, 1997. "The round-the-clock market for U.S. Treasury securities," Economic Policy Review, Federal Reserve Bank of New York, vol. 3(Jul), pages 9-32.
    24. Simon, David P., 1994. "Further evidence on segmentation in the treasury bill market," Journal of Banking & Finance, Elsevier, vol. 18(1), pages 139-151, January.
    25. George, Thomas J & Kaul, Gautam & Nimalendran, M, 1991. "Estimation of the Bid-Ask Spread and Its Components: A New Approach," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 623-656.
    26. Boni, Leslie & Leach, J Chris, 2002. "Supply Contraction and Trading Protocol: An Examination of Recent Changes in the U.S. Treasury Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(3), pages 740-762, August.
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    Citations

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    Cited by:

    1. Kitamura, Yoshihiro, 2016. "The probability of informed trading measured with price impact, price reversal, and volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 77-90.
    2. David Abad & Juan P. Sánchez-Ballesta & José Yagüe, 2017. "Audit opinions and information asymmetry in the stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(2), pages 565-595, June.
    3. Lof, Matthijs & van Bommel, Jos, 2023. "Asymmetric information and the distribution of trading volume," Journal of Corporate Finance, Elsevier, vol. 82(C).
    4. Ke, Wen-Chyan & Chen, Hueiling & Lin, Hsiou-Wei William, 2019. "A note of techniques that mitigate floating-point errors in PIN estimation," Finance Research Letters, Elsevier, vol. 31(C).
    5. 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.
    6. Jang, In Ji & Kang, Namho & Yezegel, Ari, 2022. "Common ownership, price informativeness, and corporate investment," Journal of Banking & Finance, Elsevier, vol. 135(C).
    7. Dean Katselas & Baljit K. Sidhu & Tom Smith & Chuan Yu, 2019. "Independently Certified Industry‐specific Disclosures to the Capital Market: The JORC Code in the Australian Mining Industry," Abacus, Accounting Foundation, University of Sydney, vol. 55(1), pages 128-179, March.
    8. Rahul Ravi, 2015. "Is there Asymmetric Information About Systematic Factors? Evidence from Commonality in Liquidity," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 9(2), pages 93-104.
    9. 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.
    10. 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.
    11. repec:zbw:bofrdp:2018_001 is not listed on IDEAS
    12. Lof, Matthijs & Bommel, Jos van, 2018. "Asymmetric information and the distribution of trading volume," Research Discussion Papers 1/2018, Bank of Finland.
    13. David Abad & Juan Pedro Sánchez-Ballesta & José Yagüe, 2017. "The short-term debt choice under asymmetric information," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 8(3), pages 261-285, August.
    14. David Abad & M. Fuensanta Cutillas†Gomariz & Juan Pedro Sánchez†Ballesta & José Yagüe, 2018. "Does IFRS Mandatory Adoption Affect Information Asymmetry in the Stock Market?," Australian Accounting Review, CPA Australia, vol. 28(1), pages 61-78, March.
    15. repec:zbw:bofrdp:001 is not listed on IDEAS

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    More about this item

    Keywords

    PIN; Liquidity; Asymmetric information; Informed trading;
    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

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