Research article

Forecasting ARIMA model for foreign trade statistics

Habib Ahmed Elsayir
 
Department of Mathematics, Umm AlQura University, Saudi Arabia

Author E-mail: Habibsayiroi@yahoo.com

Accepted 16 December 2014

Abstract

Time series models are applied with time series data of variables measured over time. The study focuses on examining the forecasting performance of the autoregressive Moving Average (ARIMA). The study investigates the statistical properties of the series, the residuals of the ARIMA model. The model attempts to identify the trend and statistical properties. The question studied was whether information from the proposed model gave a better trade forecast. The "forecasting" situation examined really involved added useful information. The analysis of the data demonstrates that the model applied here may be useful to understand the properties of the time series model of Saudi-US foreign trade statistics.

Keywords: ARIMA Models, Autocorrelation, Box-Jenkins Models, Correlograms, Identification.