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Comovements in Trading activity: A Multivariate Autoregressive Model of Time Series Count Data Using Copulas

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  • Erick Rengifo
  • Andresas Heinen

Abstract

This paper introduces the Multivariate Autoregressive Conditional Poisson model to deal with issues of discreteness, overdispersion and both auto- and cross-correlation, arising with multivariate counts. We model counts with a double Poisson and assume that conditionally on past observations the means follow a Vector Autoregression. We resort to copulas to introduce contemporaneous correlation. We advocate the use of our model as a feasible alternative to multivariate duration models and apply it to the study of sector and stock specific news related to the comovements in the number of trades per unit of time of the most important US department stores traded on the New York Stock Exchange. We show that the market leaders inside an specific sector, in terms of more sectorial information conveyed by their trades, are related to their size measured by their market capitalization.

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  • Erick Rengifo & Andresas Heinen, 2004. "Comovements in Trading activity: A Multivariate Autoregressive Model of Time Series Count Data Using Copulas," Econometric Society 2004 Far Eastern Meetings 755, Econometric Society.
    • Handle: RePEc:ecm:feam04:755
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    References listed on IDEAS

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    1. 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.
    2. Robert F. Engle & Asger Lunde, 2003. "Trades and Quotes: A Bivariate Point Process," Journal of Financial Econometrics, Oxford University Press, vol. 1(2), pages 159-188.
    3. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
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    Cited by:

    1. Large, Jeremy, 2007. "Measuring the resiliency of an electronic limit order book," Journal of Financial Markets, Elsevier, vol. 10(1), pages 1-25, February.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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