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An Empirical Model for Durations in Stocks

  • Simonsen, Ola

    ()

    (Department of Economics, Umeå University)

Registered author(s):

    This paper considers an extension of the univariate autoregressive conditional duration model to which durations from a second stock are added. The model is empirically used to study durations in two traded stocks, Ericsson B and AstraZeneca, on the Stockholm Stock Exchange. It is found that including durations from a second stock may add explanatory power to the univariate model. Ericsson B is Granger causing durations in AstraZeneca, while AstraZeneca is not Granger causing durations in Ericsson B. Volume, spread and trade intensity changes have significant effects for both series.

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    File URL: http://www.econ.umu.se/DownloadAsset.action?contentId=52962&languageId=3&assetKey=ues657
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    Paper provided by Umeå University, Department of Economics in its series Umeå Economic Studies with number 657.

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    Length: 23 pages
    Date of creation: 05 Apr 2005
    Date of revision:
    Handle: RePEc:hhs:umnees:0657
    Contact details of provider: Postal: Department of Economics, Umeå University, S-901 87 Umeå, Sweden
    Phone: 090 - 786 61 42
    Fax: 090 - 77 23 02
    Web page: http://www.econ.umu.se/
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    1. Kurt Brannas & Ola Simonsen, 2007. "Discretized time and conditional duration modelling for stock transaction data," Applied Financial Economics, Taylor & Francis Journals, vol. 17(8), pages 647-658.
    2. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2004. "A comparison of financial duration models via density forecast," ULB Institutional Repository 2013/136218, ULB -- Universite Libre de Bruxelles.
    3. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
    4. Engle, Robert F & Lunde, Asger, 1998. "Trades and Quotes: A Bivariate Point Process," University of California at San Diego, Economics Working Paper Series qt8bh079sq, Department of Economics, UC San Diego.
    5. 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.
    6. Serge DAROLLES & Christian GOURIÉROUX & Gaëlle LE FOL, 2000. "Intraday Transaction Price Dynamics," Annales d'Economie et de Statistique, ENSAE, issue 60, pages 207-238.
    7. Spierdijk, L. & Nijman, T.E. & van Soest, A.H.O., 2002. "Modeling Comovements in Trading Intensities to Distinguish Sector and Stock Specific News," Discussion Paper 2002-69, Tilburg University, Center for Economic Research.
    8. Grammig, Joachim & Wellner, Marc, 2002. "Modeling the interdependence of volatility and inter-transaction duration processes," Journal of Econometrics, Elsevier, vol. 106(2), pages 369-400, February.
    9. BAUWENS, Luc & GALLI, Fausto & GIOT, Pierre, 2003. "The moments of Log-ACD models," CORE Discussion Papers 2003011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
    11. 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.
    12. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," CORE Discussion Papers 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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