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Keywords:

  • Count data;
  • GARCH;
  • negative binomial;
  • observation-driven model;
  • stationarity;
  • time series
  • 62M10;
  • 62F05

This article discusses the modelling of integer-valued time series with overdispersion and potential extreme observations. For the problem, a negative binomial INGARCH model, a generalization of the Poisson INGARCH model, is proposed and stationarity conditions are given as well as the autocorrelation function. For estimation, we present three approaches with the focus on the maximum likelihood approach. Some results from numerical studies are presented and indicate that the proposed methodology performs better than the Poisson and double Poisson model-based methods.