ARIMA method is an extrapolation method for forecasting, and like any other such methods, it requires only the historical time series data for the variable under forecasting. ARIMA models are a-theoretical, implying that their construction and use are not based on any underlying theoretical...

The purpose of this paper is to construct adequate seasonal ARIMA models, using Box-Jenkins methodology, and to implement them in order to forecast short run flows of tourist arrivals and tourist overnight stays in Montenegro. Time scope covers ten years, from 2001/01 to 2010/12, while twelve...

Inflation is defined as an increase in the general price level of goods and services within a period of time. For any economic agent to formulate policy, it must taken into consideration inflation and the aim of this study is to use ARIMA model to predict inflation in Ghana. In order to fulfill...

The purpose of this paper is to compare the accuracy of the three types of models: Autoregressive Integrated Moving Average (ARIMA) models, Holt-Winters models and Neural Network Auto-Regressive (NNAR) models in forcasting the Harmonized Index of Consumer Prices (HICP) for the countries of...

In this paper, both Seasonal ARIMA and Holt-Winters models are developed to predict the monthly car sales in South Africa using data for the period of January 1994 to December 2013. The purpose of this study is to choose an optimal model suited for the sector. The three error metrics; mean...