Estimation in integer - valued moving average models

The paper presents new characterizations of the integer-valued moving average model. For four model variants we give moments and probability generating functions. Yule-Walker and conditional least squares estimators are obtained and studied by Monte Carlo simulation. A new generalized method of moment estimator based on probability generating functions is presented and shown to be consistent and asymptotically normal.The small sample performance is in some instances better than those of alternative estimators. The techniques are illustrated on a time series of traded stocks.