Scandinavian Working Papers in Economics

Umeå Economic Studies,
Umeå University, Department of Economics

No 655: Bivariate Time Series Modelling of Financial Count Data

Shahiduzzaman Quoreshi ()
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Shahiduzzaman Quoreshi: Department of Economics, Umeå University, Postal: S 901 87 Umeå, Sweden

Abstract: 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.

Keywords: Count data; Intra-day; High frequency; Time series; Estimation; Long memory; Finance

JEL-codes: C13; C22; C25; C51; G12; G14

17 pages, April 14, 2005

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