IDEAS home Printed from https://ideas.repec.org/a/eee/quaeco/v50y2010i4p538-547.html
   My bibliography  Save this article

Autocorrelation of the trade process: Evidence from the Helsinki Stock Exchange

Author

Listed:
  • Ben Sita, Bernard

Abstract

This study investigates how duration-based trading intensity modifies the first-order autocorrelation and the transitory variance of the trade process. Because prices are conditional expected values, a structural model in which the trade duration represents the rate at which prices incorporate new information is developed. This refined model is an extension of the one developed by Madhavan, Richardson, and Roomans (1997) and allows parameters characterizing the arrival rate of new information to be derived. Testing this model with data from the Helsinki Stock Exchange, I was able to determine that a model ignoring trading intensity effects on price changes would underestimate the transitory effects of the trade process. This finding suggests that trade duration captures neglected elements of implicit trading costs that increase with market microstructure effects.

Suggested Citation

  • Ben Sita, Bernard, 2010. "Autocorrelation of the trade process: Evidence from the Helsinki Stock Exchange," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 538-547, November.
    • Handle: RePEc:eee:quaeco:v:50:y:2010:i:4:p:538-547
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062-9769(10)00027-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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. 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.
    3. 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.
    4. 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.
    5. Madhavan, Ananth, 2000. "Market microstructure: A survey," Journal of Financial Markets, Elsevier, vol. 3(3), pages 205-258, August.
    6. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    7. Renault, E. & Werker, B.J.M., 2004. "Stochatic Volatility Models with Transaction Time Risk," Other publications TiSEM 06337eb0-e3eb-4d91-baeb-d, Tilburg University, School of Economics and Management.
    8. 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.
    9. Madhavan, Ananth & Richardson, Matthew & Roomans, Mark, 1997. "Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks," Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 1035-1064.
    10. 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.
    11. Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, A. Craig, 1992. "An ordered probit analysis of transaction stock prices," Journal of Financial Economics, Elsevier, vol. 31(3), pages 319-379, June.
    12. Ahn, Hee-Joon & Cai, Jun & Hamao, Yasushi & Ho, Richard Y. K., 2002. "The components of the bid-ask spread in a limit-order market: evidence from the Tokyo Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 9(4), pages 399-430, November.
    13. Spierdijk, Laura, 2004. "An empirical analysis of the role of the trading intensity in information dissemination on the NYSE," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 163-184, March.
    14. Aitken, Michael & Comerton-Forde, Carole, 2003. "How should liquidity be measured?," Pacific-Basin Finance Journal, Elsevier, vol. 11(1), pages 45-59, January.
    15. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
    16. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    17. Hasbrouck, Joel, 1993. "Assessing the Quality of a Security Market: A New Approach to Transaction-Cost Measurement," Review of Financial Studies, Society for Financial Studies, vol. 6(1), pages 191-212.
    18. Roll, Richard, 1984. "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
    19. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bowe, Michael & Hyde, Stuart & McFarlane, Lavern, 2013. "Duration, trading volume and the price impact of trades in an emerging futures market," Emerging Markets Review, Elsevier, vol. 17(C), pages 89-105.
    2. Kalaitzoglou, Iordanis & Ibrahim, Boulis Maher, 2013. "Trading patterns in the European carbon market: The role of trading intensity and OTC transactions," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(4), pages 402-416.

    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. Ferriani, Fabrizio, 2010. "Informed and uninformed traders at work: evidence from the French market," MPRA Paper 24487, University Library of Munich, Germany.
    2. Ibrahim, Boulis Maher & Kalaitzoglou, Iordanis Angelos, 2016. "Why do carbon prices and price volatility change?," Journal of Banking & Finance, Elsevier, vol. 63(C), pages 76-94.
    3. Ben Sita, Bernard & Westerholm, P. Joakim, 2011. "The role of trading intensity estimating the implicit bid–ask spread and determining transitory effects," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 306-310.
    4. 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).
    5. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    6. Pascual, Roberto & Escribano, Álvaro & Tapia, Mikel, 2000. "Adverse selection costs, trading activity and liquidity in the NYSE: an empirical analysis in a dynamic context," UC3M Working papers. Economics 7276, Universidad Carlos III de Madrid. Departamento de Economía.
    7. Chen, Tao & Li, Jie & Cai, Jun, 2008. "Information content of inter-trade time on the Chinese market," Emerging Markets Review, Elsevier, vol. 9(3), pages 174-193, September.
    8. Ahn, Hee-Joon & Cai, Jun & Hamao, Yasushi & Ho, Richard Y.K., 2005. "Adverse selection, brokerage coverage, and trading activity on the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 29(6), pages 1483-1508, June.
    9. 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.
    10. 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).
    11. Bowe, Michael & Hyde, Stuart & McFarlane, Lavern, 2013. "Duration, trading volume and the price impact of trades in an emerging futures market," Emerging Markets Review, Elsevier, vol. 17(C), pages 89-105.
    12. Maria Pacurar, 2008. "Autoregressive Conditional Duration Models In Finance: A Survey Of The Theoretical And Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 22(4), pages 711-751, September.
    13. Ahn, Hee-Joon & Cai, Jun & Hamao, Yasushi & Ho, Richard Y. K., 2002. "The components of the bid-ask spread in a limit-order market: evidence from the Tokyo Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 9(4), pages 399-430, November.
    14. Wong, Woon K. & Tan, Dijun & Tian, Yixiang, 2009. "Informed trading and liquidity in the Shanghai Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 66-73, March.
    15. Engle, Robert F. & Patton, Andrew J., 2004. "Impacts of trades in an error-correction model of quote prices," Journal of Financial Markets, Elsevier, vol. 7(1), pages 1-25, January.
    16. Jondeau, Eric & Lahaye, Jérôme & Rockinger, Michael, 2015. "Estimating the price impact of trades in a high-frequency microstructure model with jumps," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 205-224.
    17. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    18. Jun (Tony) Ruan & Tongshu Ma, 2017. "Bid-Ask Spread, Quoted Depths, and Unexpected Duration Between Trades," Journal of Financial Services Research, Springer;Western Finance Association, vol. 51(3), pages 385-436, June.
    19. 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.
    20. Biais, Bruno & Glosten, Larry & Spatt, Chester, 2005. "Market microstructure: A survey of microfoundations, empirical results, and policy implications," Journal of Financial Markets, Elsevier, vol. 8(2), pages 217-264, May.

    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:eee:quaeco:v:50:y:2010:i:4:p:538-547. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620167 .

    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.