IDEAS home Printed from https://ideas.repec.org/p/qld/uq2004/411.html
   My bibliography  Save this paper

No Trade, Informed Trading, and Accuracy of Information

Author

Abstract

We present a model in which there is uncertainty about realization of a risky asset value for an informed trader. Then, we show that the informed trader does not trade in equi- librium if the inside information the informed trader has is not sufficiently accurate. We use the framework presented by Glosten and Milgrom (1985) and extend the assumption that the informed trader knows the terminal value of the risky asset. Finally, we obtain the conditions under which the informed trader would not trade in equilibrium.

Suggested Citation

  • Jayanaka Wijeratne & Shino Takayama, 2010. "No Trade, Informed Trading, and Accuracy of Information," Discussion Papers Series 411, School of Economics, University of Queensland, Australia.
  • Handle: RePEc:qld:uq2004:411
    as

    Download full text from publisher

    File URL: https://economics.uq.edu.au/files/44757/411.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jones, Charles M & Kaul, Gautam & Lipson, Marc L, 1994. "Transactions, Volume, and Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 631-651.
    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. Fischer, Andreas M. & Ranaldo, Angelo, 2011. "Does FOMC news increase global FX trading?," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2965-2973, November.
    2. Koski, Jennifer Lynch, 1998. "Measurement Effects and the Variance of Returns after Stock Splits and Stock Dividends," The Review of Financial Studies, Society for Financial Studies, vol. 11(1), pages 143-162.
    3. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    4. Doureige J. Jurdi, 2020. "Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    5. Malay K. Dey & B. Radhakrishna (Radha), 2007. "Who Trades Around Earnings Announcements? Evidence from TORQ Data," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(1‐2), pages 269-291, January.
    6. Gerhard, Frank & Hess, Dieter & Pohlmeier, Winfried, 1998. "What a Difference a Day Makes: On the Common Market Microstructure of Trading Days," CoFE Discussion Papers 98/01, University of Konstanz, Center of Finance and Econometrics (CoFE).
    7. Allaudeen Hameed, 1997. "Time-Varying Factors And Cross-Autocorrelations In Short-Horizon Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 20(4), pages 435-458, December.
    8. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    9. Craig Pirrong, 1996. "Market liquidity and depth on computerized and open outcry trading systems: A comparison of DTB and LIFFE bund contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(5), pages 519-543, August.
    10. Misund, Bård & Oglend, Atle, 2016. "Supply and demand determinants of natural gas price volatility in the U.K.: A vector autoregression approach," Energy, Elsevier, vol. 111(C), pages 178-189.
    11. Bacidore, Jeffrey M. & Battalio, Robert & Galpin, Neal & Jennings, Robert, 2005. "Sources of liquidity for NYSE-listed non-US stocks," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3075-3098, December.
    12. Lundstrum, Leonard L. & Walker, Mark D., 2006. "LEAPS introductions and the value of the underlying stocks," Journal of Financial Intermediation, Elsevier, vol. 15(4), pages 494-510, October.
    13. Menkhoff, Lukas & Schmeling, Maik, 2010. "Trader see, trader do: How do (small) FX traders react to large counterparties' trades?," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1283-1302, November.
    14. Chen, Chun-nan, 2013. "The predictability of opening returns for the returns of the trading day: Evidence from Taiwan futures market," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 272-281.
    15. Alexander, Gordon J. & Peterson, Mark A., 2007. "An analysis of trade-size clustering and its relation to stealth trading," Journal of Financial Economics, Elsevier, vol. 84(2), pages 435-471, May.
    16. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
    17. Martin D. D. Evans, 2017. "FX Trading and Exchange Rate Dynamics," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 5, pages 189-245, World Scientific Publishing Co. Pte. Ltd..
    18. Martin Evans and Richard K. Lyons, 2002. "Are Different-Currency Assets Imperfect Substitutes?," Working Papers gueconwpa~02-02-12, Georgetown University, Department of Economics.
    19. Jeffrey R. Black & Pankaj K. Jain & Wei Sun, 2023. "Trade-time clustering," Review of Quantitative Finance and Accounting, Springer, vol. 60(3), pages 1209-1242, April.
    20. Vaalmikki Argoon & Spiros Bougheas & Chris Milner, 2013. "Lead-Lag Relationships and Institutional Ownership: Evidence from an Embryonic Equity Market," Discussion Papers 2013/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).

    More about this item

    JEL classification:

    • G0 - Financial Economics - - General
    • D4 - Microeconomics - - Market Structure, Pricing, and Design

    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:qld:uq2004:411. 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: SOE IT (email available below). General contact details of provider: https://edirc.repec.org/data/decuqau.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.