We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed on high frequencies, such as cumulated trading volumes or the time between potentially...

We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed on high frequencies, such as cumulated trading volumes or the time between potentially...

In this paper a flexible model for correlation in high frequency data is proposed, which maintains the data's discrete nature and captures features such as asymmetry and excess zeros. The model uses an a theoretical approach based on that of an ARIMA model. This model works with price changes...

Lately the interest in arranging festivals or special events has increased in many cities. In this paper we present an econometric model to account for the tourism accommodation impact of such events. The autoregressive count data model incorporates some of the more important factors in the...

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...