This short paper proposes a simultaneous equations model formulation for time series of count data. Some of the basic moment properties of the model are obtained. The inclusion of real valued exogenous variables is suggested to be through the parameters of the model. Some remarks on the...

A model to account for the long memory property in a count data framework <p> is proposed and applied to high frequency stock transactions data. <p> The unconditional and conditional first and second order moments are <p> given. The CLS and FGLS estimators are discussed. In its empirical <p> application to...</p></p></p></p>

The integer-valued AR(1) model is generalized to encompass some of the more likely features of economic time series of count data. The generalizations come at the price of loosing exact distributional properties. For most specifications the first and second order both conditional and...

Estimation in nonlinear time series models has mainly been performed by least squares or maximum likelihood (ML) methods. The paper suggests and studies the performance of generalized method of moments (GMM) and indirect estimators for the autoregressive asymmetric moving average model. Both...

The impact of news of the Moscow and New York stock market exchanges on the <p> returns and volatilities of the Baltic state stock market indices is studied using daily <p> return data for the period of 2000-2005. A nonlinear time series model that accounts <p> for asymmetries in the conditional mean and...</p></p></p>

This thesis comprises four papers concerning modelling of financial count data. Paper [1], [2] <p> and [3] advance the integer-valued moving average model (INMA), a special case of integer-valued <p> autoregressive moving average (INARMA) model class, and apply the models to the number of <p> stock...</p></p></p>

The paper considers conditional duration models in which durations are in continuous time but measured in grouped or discretized form. This feature of recorded durations in combination with a frequently traded stock is expected to negatively influence the performance of conventional estimators....

The paper introduces a new approach to incorporating time dependent overdispersion for Poisson related regression models. To handle the added flexibility in conditional heteroskedasticity in time series count data some wellknown estimators are adapted and a GMM type estimator is suggested. The...