Decision Science Letters · 2019 · 33 citations · 1 references
ComputingEconomicsForecastingPredictive AnalyticsTime Series AnalysisEconomic ForecastingForecasting MethodsTime Series EconometricsTime Series ForecastingTime Series ModelingTime Series PredictionArima ModelsAutoregressive Integrated Moving AverageAutoregressive Integrated Moving Average ForecastingAutoregressive Moving Average ModelsEconometric Forecasting ModelsNeural ForecastingNeural Network ModelingNeural Time Series Forecasting
Nowadays, Saudi government has established several strategic tactics such as Saudi Vision 2030 to predict the future of the country. In order to accomplish a superior growth in the economy of the country, mathematical model and forecasting techniques are important tools. In this study, total annual exports and imports of the Kingdom of Saudi Arabia are forecasted using Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) models. This paper tries to predict a time series data using ANN and ARIMA models on total annual exports and imports of Kingdom of Saudi Arabia from the year 1968 to the year 2017 with the help of statistical software XLSTAT. The applied models are used to predict some future values of total annual exports and imports of the Kingdom of Saudi Arabia. It is found that the ANN and ARIMA (1, 1, 2) and ARIMA (0, 1, 1) models are suitable for predicting the total annual exports and imports of the Kingdom of Saudi Arabia.
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