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A PIN per day shows what news convey: the intraday probability of informed trading

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Listed:
  • Thomas Pöppe

    (Technische Universität Darmstadt)

  • Michael Aitken

    (Capital Markets CRC Ltd.)

  • Dirk Schiereck

    (Technische Universität Darmstadt)

  • Ingo Wiegand

    (Stanford University)

Abstract

This paper develops a new intraday estimation procedure for the sequential microstructure trading model initially proposed by Easley et al. (Rev Financ Stud 10:805–835, 1997a). Using a full year of intraday trading data for the top 100 German stocks, we demonstrate how the new estimation procedure eliminates or significantly reduces the shortcomings of the original approach in recent, high-frequency trading environments. We slice a trading day in buckets of several minutes’ length to obtain one estimate of the composite variable probability of informed trading (PIN) per day. This approach makes PIN applicable in short horizon event studies. Convergence rates are above 95 % even for the most liquid stocks and the model’s underlying assumptions of independence for the arrival of traders and information events are fulfilled to a much higher degree than in the original approach. An empirical application in an event study type setting demonstrates how official announcements stipulated in German insider trading legislation significantly reduce information asymmetry upon public disclosure.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:rqfnac:v:47:y:2016:i:4:d:10.1007_s11156-015-0535-z
    DOI: 10.1007/s11156-015-0535-z
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    1. Jackson, David, 2013. "Estimating PIN for firms with high levels of trading," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 116-120.
    2. Raman Kumar & Marius Popescu, 2014. "The implied intra-day probability of informed trading," Review of Quantitative Finance and Accounting, Springer, vol. 42(2), pages 357-371, February.
    3. Grammig, Joachim & Theissen, Erik & Wuensche, Oliver, 2007. "Time and price impact of a trade: A structural approach," CFR Working Papers 07-12, University of Cologne, Centre for Financial Research (CFR).
    4. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    5. Utpal Bhattacharya & Hazem Daouk, 2002. "The World Price of Insider Trading," Journal of Finance, American Finance Association, vol. 57(1), pages 75-108, February.
    6. 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.
    7. Yan, Yuxing & Zhang, Shaojun, 2012. "An improved estimation method and empirical properties of the probability of informed trading," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 454-467.
    8. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, vol. 55(6), pages 2467-2498, December.
    9. 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.
    10. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    11. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    12. William Lin, Hsiou-Wei & Ke, Wen-Chyan, 2011. "A computing bias in estimating the probability of informed trading," Journal of Financial Markets, Elsevier, vol. 14(4), pages 625-640, November.
    13. Green, T. Clifton, 2006. "The Value of Client Access to Analyst Recommendations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(1), pages 1-24, March.
    14. 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, Oxford University Press, vol. 7(3), pages 288-311, Summer.
    15. Kim, Sok Tae & Lin, Ji-Chai & Slovin, Myron B., 1997. "Market Structure, Informed Trading, and Analysts' Recommendations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(4), pages 507-524, December.
    16. Hachmeister, A. & Schiereck, D., 2010. "Dancing in the Dark: Post-trade Anonymity, Liquidity, and Informed Trading," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 34883, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    17. Ellis, Katrina & Michaely, Roni & O'Hara, Maureen, 2000. "The Accuracy of Trade Classification Rules: Evidence from Nasdaq," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(4), pages 529-551, December.
    18. Easley, David & O'Hara, Maureen & Paperman, Joseph, 1998. "Financial analysts and information-based trade," Journal of Financial Markets, Elsevier, vol. 1(2), pages 175-201, August.
    19. Pierre Collin-Dufresne & Vyacheslav Fos, 2012. "Do prices reveal the presence of informed trading?," NBER Working Papers 18452, National Bureau of Economic Research, Inc.
    20. Andersen, Torben G. & Bondarenko, Oleg, 2014. "VPIN and the flash crash," Journal of Financial Markets, Elsevier, vol. 17(C), pages 1-46.
    21. Grammig, Joachim & Schiereck, Dirk & Theissen, Erik, 2001. "Knowing me, knowing you: : Trader anonymity and informed trading in parallel markets," Journal of Financial Markets, Elsevier, vol. 4(4), pages 385-412, October.
    22. Muntermann, Jan & Guettler, Andre, 2007. "Intraday stock price effects of ad hoc disclosures: the German case," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(1), pages 1-24, February.
    23. Lei, Qin & Wu, Guojun, 2005. "Time-varying informed and uninformed trading activities," Journal of Financial Markets, Elsevier, vol. 8(2), pages 153-181, May.
    24. Easley, David & O'Hara, Maureen & Saar, Gideon, 2001. "How Stock Splits Affect Trading: A Microstructure Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(1), pages 25-51, March.
    25. Vega, Clara, 2006. "Stock price reaction to public and private information," Journal of Financial Economics, Elsevier, vol. 82(1), pages 103-133, October.
    26. Easley, David, et al, 1996. "Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    27. Busse, Jeffrey A. & Clifton Green, T., 2002. "Market efficiency in real time," Journal of Financial Economics, Elsevier, vol. 65(3), pages 415-437, September.
    28. Alexandra Hachmeister & Dirk Schiereck, 2010. "Dancing in the dark: post-trade anonymity, liquidity and informed trading," Review of Quantitative Finance and Accounting, Springer, vol. 34(2), pages 145-177, February.
    29. David Easley & Robert F. Engle & Maureen O'Hara & Liuren Wu, 2008. "Time-Varying Arrival Rates of Informed and Uninformed Trades," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 171-207, Spring.
    30. Nuno Fernandes & Miguel A. Ferreira, 2009. "Insider Trading Laws and Stock Price Informativeness," Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1845-1887, May.
    31. Charles Chang & Emily Lin, 2014. "On the Determinants of Basis Spread for Taiwan Index Futures and the Role of Speculators," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-30.
    32. William Cheung & Kejing Liu, 2014. "A Comparison of China's Main Board and Growth Enterprise Market Board — Market Microstructure Approach," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-29.
    33. 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.
    34. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    35. Easley, David & O'Hara, Maureen, 1992. "Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
    36. 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.
    37. Miao Luo & Tao Chen & Isabel Yan, 2014. "Price informativeness and institutional ownership: evidence from Japan," Review of Quantitative Finance and Accounting, Springer, vol. 42(4), pages 627-651, May.
    38. Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
    39. 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.
    40. 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.
    41. Heidle, Hans G. & Huang, Roger D., 2002. "Information-Based Trading in Dealer and Auction Markets: An Analysis of Exchange Listings," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(3), pages 391-424, September.
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    More about this item

    Keywords

    Capital markets; Probability of informed trading; Information asymmetry; High-frequency trading; Insider trading regulation;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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