IDEAS home Printed from https://ideas.repec.org/p/cdf/wpaper/2008-12.html

The Other Side of the Trading Story: Evidence from NYSE

Author

Listed:
  • Wong, Woon K

    (Cardiff Business School)

  • Copeland, Laurence

    (Cardiff Business School)

  • Lu, Ralph

Abstract

We analyse the well-known TORQ dataset of trades on the NYSE over a 3-month period, breaking down transactions depending on whether the active or passive side was institutional or private. This allows us to compare the returns on the different trade categories. We find that, however we analyse the results, institutions are best informed, and earn highest returns when trading with individuals as counter party. We also confirm the conclusions found elsewhere in the literature that informed traders often place limit orders, especially towards the end of the day (as predicted on the basis of laboratory experiments in Bloomfield, O.Hara, and Saar (2005)). Finally, we find that trading between institutions accounts for the bulk of trading volume, but carries little information and seems to be largely liquidity-driven.

Suggested Citation

  • Wong, Woon K & Copeland, Laurence & Lu, Ralph, 2008. "The Other Side of the Trading Story: Evidence from NYSE," Cardiff Economics Working Papers E2008/12, Cardiff University, Cardiff Business School, Economics Section.
    • Handle: RePEc:cdf:wpaper:2008/12
    as

    Download full text from publisher

    File URL: http://carbsecon.com/wp/E2008_12.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    2. 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.
    3. Kandel, Eugene & Pearson, Neil D, 1995. "Differential Interpretation of Public Signals and Trade in Speculative Markets," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 831-872, August.
    4. 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.
    5. Glosten, Lawrence R, 1994. "Is the Electronic Open Limit Order Book Inevitable?," Journal of Finance, American Finance Association, vol. 49(4), pages 1127-1161, September.
    6. 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.
    7. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    8. Harris, Lawrence E. & Panchapagesan, Venkatesh, 2005. "The information content of the limit order book: evidence from NYSE specialist trading decisions," Journal of Financial Markets, Elsevier, vol. 8(1), pages 25-67, February.
    9. Hasbrouck, Joel, 1991. "The Summary Informativeness of Stock Trades: An Econometric Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 571-595.
    10. repec:bla:jfinan:v:59:y:2004:i:4:p:1553-1583 is not listed on IDEAS
    11. 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.
    12. Lee, Yi-Tsung & Lin, Ji-Chai & Liu, Yu-Jane, 1999. "Trading patterns of big versus small players in an emerging market: An empirical analysis," Journal of Banking & Finance, Elsevier, vol. 23(5), pages 701-725, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
    2. 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.
    3. Lamoureux, Christopher G. & Wang, Qin, 2015. "Measuring private information in a specialist market," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 92-119.
    4. Van Ness, Bonnie & Van Ness, Robert & Yildiz, Serhat, 2021. "Private information in trades, R2, and large stock price movements," Journal of Banking & Finance, Elsevier, vol. 131(C).
    5. Lei, Qin & Wu, Guojun, 2005. "Time-varying informed and uninformed trading activities," Journal of Financial Markets, Elsevier, vol. 8(2), pages 153-181, May.
    6. Duarte, Jefferson & Hu, Edwin & Young, Lance, 2020. "A comparison of some structural models of private information arrival," Journal of Financial Economics, Elsevier, vol. 135(3), pages 795-815.
    7. Jagjeev Dosanjh, 2017. "Exchange Initiatives and Market Efficiency: Evidence from the Australian Securities Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2017, January-A.
    8. Bardong, Florian & Bartram, Söhnke M. & Yadav, Pradeep K., 2006. "The Effect of Corporate Break-ups on Information Asymmetry: A Market Microstructure Analysis," MPRA Paper 13155, University Library of Munich, Germany, revised 26 Oct 2008.
    9. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    10. repec:uts:finphd:34 is not listed on IDEAS
    11. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
    12. Perotti, Pietro & Rindi, Barbara, 2010. "Market makers as information providers: The natural experiment of STAR," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 895-917, December.
    13. 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.
    14. Sun, Yuxin & Ibikunle, Gbenga, 2017. "Informed trading and the price impact of block trades: A high frequency trading analysis," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 114-129.
    15. Chang, Sanders S. & Wang, F. Albert, 2015. "Adverse selection and the presence of informed trading," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 19-33.
    16. Gary McCormick & Dan W. French, 2016. "Effects of frequent information disclosure: the case of daily net asset value reporting for closed-end investment companies," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 107-122, January.
    17. Mazza, Paolo, 2015. "Price dynamics and market liquidity: An intraday event study on Euronext," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 139-153.
    18. Cosmin Octavian Cepoi & Victor Dragotă & Ruxandra Trifan & Andreea Iordache, 2023. "Probability of informed trading during the COVID-19 pandemic: the case of the Romanian stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    19. Morris, Jeremy & Xu, Ke, 2025. "The effect of NYSE American’s latency delay on informed trading," International Review of Financial Analysis, Elsevier, vol. 105(C).
    20. Cosmin Octavian Cepoi & Filip Mihai Toma, 2016. "Estimating Probability of Informed Trading on the Bucharest Stock Exchange," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(2), pages 140-160, April.
    21. Diego Alonso Agudelo Rueda & Edwin Villarraga & Santiago Giraldo, 2012. "Asimetría en la información y su efecto en los rendimientos en los mercados accionarios latinoamericanos," Documentos de Trabajo de Valor Público 10669, Universidad EAFIT.

    More about this item

    Keywords

    ;
    ;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdf:wpaper:2008/12. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Yongdeng Xu (email available below). General contact details of provider: https://edirc.repec.org/data/ecscfuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.