IDEAS home Printed from https://ideas.repec.org/a/oup/rfinst/v10y1997i3p805-35.html
   My bibliography  Save this article

One Day in the Life of a Very Common Stock

Author

Listed:
  • Easley, David
  • Kiefer, Nicholas M
  • O'Hara, Maureen

Abstract

Using the model structure of Easley and O'Hara, we demonstrate how the parameters of the market-maker's beliefs can be estimated from trade data. We show how to extract information from both trade and no-trade intervals, and how intraday and interday data provide information. We derive and evaluate tests of model specification and estimate the information content of differential trade sizes. Our work provides a framework for testing extant microstructure models, shows how to extract the information contained in the trading process, and demonstrates the empirical importance of asymmetric information models for asset prices. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

Suggested Citation

  • 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.
  • Handle: RePEc:oup:rfinst:v:10:y:1997:i:3:p:805-35
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Devine, Theresa J. & Kiefer, Nicolas M., 1991. "Empirical Labor Economics: The Search Approach," OUP Catalogue, Oxford University Press, number 9780195059366.
    2. Foster, F Douglas & Viswanathan, S, 1995. "Can Speculative Trading Explain the Volume-Volatility Relation?," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 379-396, October.
    3. 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.
    4. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    5. 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.
    6. 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.
    7. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    8. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    9. 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.
    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. 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.
    2. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    3. 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.
    4. Gourieroux, Christian & Jasiak, Joanna & Le Fol, Gaelle, 1999. "Intra-day market activity," Journal of Financial Markets, Elsevier, vol. 2(3), pages 193-226, August.
    5. Múnera, Daimer J. & Agudelo, Diego A., 2022. "Who moved my liquidity? Liquidity evaporation in emerging markets in periods of financial uncertainty," Journal of International Money and Finance, Elsevier, vol. 129(C).
    6. Jinliang Li & Chunchi Wu, 2006. "Daily Return Volatility, Bid-Ask Spreads, and Information Flow: Analyzing the Information Content of Volume," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2697-2740, September.
    7. Hartmann, Philipp, 1999. "Trading volumes and transaction costs in the foreign exchange market: Evidence from daily dollar-yen spot data," Journal of Banking & Finance, Elsevier, vol. 23(5), pages 801-824, May.
    8. Chan, Choon Chat & Fong, Wai Mun, 2006. "Realized volatility and transactions," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2063-2085, July.
    9. Arango, Ignacio & Agudelo, Diego A., 2019. "How does information disclosure affect liquidity? Evidence from an emerging market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    10. Ignacio Arango & Diego A. Agudelo, 2017. "How does information disclosure affect liquidity?Evidence from an Emerging Market," Documentos de Trabajo de Valor Público 16990, Universidad EAFIT.
    11. Diego A. Agudelo & Ignacio Arango, 2017. "How does information disclosure affect liquidity? Evidence from an Emerging Market," Documentos de Trabajo de Valor Público 16944, Universidad EAFIT.
    12. Dufour, Alfonso & Engle, Robert F, 1999. "Time and the Price Impact of a Trade," University of California at San Diego, Economics Working Paper Series qt62c0h04j, Department of Economics, UC San Diego.
    13. 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.
    14. Pascual, Roberto, 1999. "How does liquidity behave? A multidimensional analysis of NYSE stocks," DEE - Working Papers. Business Economics. WB 6433, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    15. 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.
    16. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    17. Danilova, Albina & Julliard, Christian, 2014. "Information asymmetries, volatility, liquidity, and the Tobin Tax," LSE Research Online Documents on Economics 60957, London School of Economics and Political Science, LSE Library.
    18. Lyons, Richard K., 1995. "Tests of microstructural hypotheses in the foreign exchange market," Journal of Financial Economics, Elsevier, vol. 39(2-3), pages 321-351.
    19. Slim, Skander & Dahmene, Meriam, 2016. "Asymmetric information, volatility components and the volume–volatility relationship for the CAC40 stocks," Global Finance Journal, Elsevier, vol. 29(C), pages 70-84.
    20. Lei, Qin & Wu, Guojun, 2005. "Time-varying informed and uninformed trading activities," Journal of Financial Markets, Elsevier, vol. 8(2), pages 153-181, May.

    More about this item

    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:oup:rfinst:v:10:y:1997:i:3:p:805-35. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/sfsssea.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.