A Comparative study on ARIMA model and Exponential smoothing method in time series forecasting

تهدف هذه الدراسة إلى المقارنة بين نماذج Arima وطريقة التمهيد الأسي بالتنبؤ في السلاسل الزمنية، كما نسلط الضوء على مفاهيم الأساسية الخاصة بمنهجية ARIMA وطريقة التمهيد الأسي. ركزت الدراسة على التنبؤ بالسلاسل الزمنية ذات النطاق الضيق بين نقطة وأخرى ذات نطاق واسع بالاضافة إلى استخدام أطوال مختلفة من فترات التنبؤ وقد تم استخدام معيار RMSE للمقارنة بين الطريقتين.

The study aims at comparing ARIMA models and the exponential smoothing method in forecasting. This study also highlights the special and basic concepts of ARIMA model and the exponential smoothing method. The comparison focuses on the ability of both methods to forecast the time series with a narrow range of one point to another and the time series with a long range of one point to another, and also on the different lengths of the forecasting periods. Currency exchange rates of Shekel to American dollar were used to make this comparison in the period between 25/1/2010 to 22/10/2016. In addition, weekly gold prices were considered in the period between 10/1/2010 to 23/10/2016. RMSE standard was used in order to compare between both methods. In this study, the researcher came up with the conclusion that ARIMA models give a better forecasting for the time series with a long range of one point to another and for long term forecasting, but cannot produce a better forecasting for time series with a narrow range of one point to another as in currency exchange prices. On the contrary, exponential smoothing method can give better forecasting for Exchange Rates that has a narrow range of one point to another for its time series, while it cannot give better forecasting for long term forecasting periods