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Bivariate Time Series Modelling of Financial Count Data

  • Quoreshi, Shahiduzzaman


    (Department of Economics, Umeå University)

A bivariate integer-valued moving average (BINMA) model is proposed. The BINMA model allows for both positive and negative correlation between the counts. This model can be seen as an inverse of the conditional duration model in the sense that short durations in a time interval correspond to a large count and vice versa. The conditional mean, variance and covariance of the BINMA model are given. Model extensions to include explanatory variables are suggested. Using the BINMA model for AstraZeneca and Ericsson B it is found that there is positive correlation between the stock transactions series. Empirically, we find support for the use of long-lag bivariate moving average models for the two series. have significant effects for both series.

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Paper provided by Umeå University, Department of Economics in its series Umeå Economic Studies with number 655.

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Length: 17 pages
Date of creation: 14 Apr 2005
Date of revision:
Handle: RePEc:hhs:umnees:0655
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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