Two classes of dynamic binomial integer-valued ARCH models

Abstract

This paper introduces two classes of binomial integer-valued ARCH models with dynamic survival probabilities, each of which is controlled by a stochastic recurrence equation. Stationarity and ergodicity of the process are established, and stochastic properties are given. Conditional least squares and conditional maximum likelihood estimators for the parameters of interest are considered, and their large-sample properties are established. The performances of these estimators are compared via simulation studies. Finally, we demonstrate the usefulness of the proposed models by analyzing real datasets.