Time series data: The application of arima model of business

Auto-Regressive Integrated Moving Average (ARIMA) Models are among the most important time series models used in businesses and financial market forecasting over the past decades.

Theoretically, and empirically, findings have suggested that integration of different models can be an effective method of improving upon their predictive performance, especially when the models in the ensemble are quite different. In this paper, ARIMA models are viewed from the introduction, looking at the definitions, assumptions, general notations of ARIMA models; and also the procedure of ARIMA with respect to the three stages of ARIMA modeling ‘cum’ procedural statements are considered. And we demonstrate the use of ARIMA procedure statements. We demonstrate also that ARIMA model is a complex mathematical or statistical technique for forecasting business variables.