IDEAS home Printed from
   My bibliography  Save this article

The logarithmic ACD model: The microstructure of the German and Polish stock markets


  • Henryk Gurgul

    () (AGH University of Science and Technology, Department of Applications of Mathematics in Economics)

  • Robert Syrek

    () (Jagiellonian University in Kraków, Institute of Economics, Finance and Management)


The main goal of this paper is to compare the microstructure of selected stocks listed on theFrankfurt and Warsaw Stock Exchanges. We focus on the properties of duration on both markets and on fitting the appropriate ACD models. Because of the quite different levels of capitalization of stocks on these markets, we observe essential discrepancies between these stocks. Whilefor most German companies on the DAX30, the Burr distribution fits better than generalized gamma distribution, the latter distribution is superior in the case of the largest Polish companies. Analyzing series by hazard function, we note the similarity of hazard functions for companies on both markets, which tend to have a U-shaped pattern.

Suggested Citation

  • Henryk Gurgul & Robert Syrek, 2016. "The logarithmic ACD model: The microstructure of the German and Polish stock markets," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 17(1), pages 77-92.
  • Handle: RePEc:agh:journl:v:17:y:2016:i:1:p:77-92

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Michael Goldstein & Gregory Laughlin & Anthony Aguirre & Joseph Grundfest, 2014. "Information Transmission between Financial Markets in Chicago and New York," The Financial Review, Eastern Finance Association, vol. 49(2), pages 283-312, May.
    2. Hasbrouck, Joel & Saar, Gideon, 2009. "Technology and liquidity provision: The blurring of traditional definitions," Journal of Financial Markets, Elsevier, vol. 12(2), pages 143-172, May.
    3. 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.
    4. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
    5. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    6. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    7. repec:adr:anecst:y:2000:i:60 is not listed on IDEAS
    8. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    9. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
    10. Brogaard, Jonathan & Garriott, Corey, 2019. "High-Frequency Trading Competition," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(04), pages 1469-1497, August.
    11. Michael Goldstein & Michael A. Goldstein & Pavitra Kumar & Frank C. Graves, 2014. "Computerized and High-Frequency Trading," The Financial Review, Eastern Finance Association, vol. 49(2), pages 177-202, May.
    12. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    13. repec:wsi:qjfxxx:v:01:y:2011:i:01:n:s2010139211000067 is not listed on IDEAS
    14. Luc Bauwens & Pierre Giot, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
    15. Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
    16. repec:adr:anecst:y:2000:i:60:p:05 is not listed on IDEAS
    17. Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 16-38.
    Full references (including those not matched with items on IDEAS)


    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:agh:journl:v:17:y:2016:i:1:p:77-92. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lukasz Lach). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.