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An Empirical Model for Durations in Stocks

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  • Simonsen, Ola

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    (Department of Economics, Umeå University)

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    Abstract

    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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    Bibliographic Info

    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
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    Web page: http://www.econ.umu.se/
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    Related research

    Keywords: multivariate; duration; transaction data; market microstructure;

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    References

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    1. 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.
    2. 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.
    3. Spierdijk, L. & Nijman, T.E. & Soest, A.H.O. van, 2002. "Modeling Comovements in Trading Intensities to Distinguish Sector and Stock Specific News," Discussion Paper 2002-69, Tilburg University, Center for Economic Research.
    4. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
    5. Robert F. Engle & Asger Lunde, 2003. "Trades and Quotes: A Bivariate Point Process," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(2), pages 159-188.
    6. Brännäs, Kurt & Simonsen, Ola, 2003. "Discretized Time and Conditional Duration Modelling for Stock Transaction Data," UmeÃ¥ Economic Studies 610, Umeå University, Department of Economics.
    7. BAUWENS, Luc & GALLi, Fausto & GIOT, Pierre, . "The moments of Log-ACD models," CORE Discussion Papers RP -2023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. 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).
    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.
    10. 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.
    11. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
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    Citations

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    Cited by:
    1. Simonsen, Ola, 2006. "The Impact of News Releases on Trade Durations in Stocks -Empirical Evidence from Sweden," UmeÃ¥ Economic Studies 688, Umeå University, Department of Economics.
    2. Simonsen, Ola, 2006. "Stock Data, Trade Durations, And Limit Order Book Information," UmeÃ¥ Economic Studies 689, Umeå University, Department of Economics.

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