Box-Jenkins Forecasting Arima Models as Applied to Commercial Banks' Deposits
Ibrahim, I. (1992). Box-Jenkins Forecasting Arima Models as Applied to Commercial Banks' Deposits. EKB Journal Management System, 36(2), 234-254. doi: 10.21608/esju.1992.314864
Ibrahim Hassan Ibrahim. "Box-Jenkins Forecasting Arima Models as Applied to Commercial Banks' Deposits". EKB Journal Management System, 36, 2, 1992, 234-254. doi: 10.21608/esju.1992.314864
Ibrahim, I. (1992). 'Box-Jenkins Forecasting Arima Models as Applied to Commercial Banks' Deposits', EKB Journal Management System, 36(2), pp. 234-254. doi: 10.21608/esju.1992.314864
Ibrahim, I. Box-Jenkins Forecasting Arima Models as Applied to Commercial Banks' Deposits. EKB Journal Management System, 1992; 36(2): 234-254. doi: 10.21608/esju.1992.314864

Box-Jenkins Forecasting Arima Models as Applied to Commercial Banks' Deposits

The Egyptian Statistical Journal
Article 6, Volume 36, Issue 2, December 1992, Page 234-254  XML
Document Type: Original Article
DOI: 10.21608/esju.1992.314864
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Author
Ibrahim Hassan Ibrahim
Abstract
The Box-Jenkins ARIMA model is used in this article to identify statistical forecasting models for the commercial banks deposits in Egypt. Four models have been identified according to the type of the sun deposits. For every type of deposit two sets of data have been considered, monthly and quarterly. The time-series analysis for both demand and savings deposits demand are shows that nonstationary seasonal time-series. The demand deposits have been identified to be an ARIMA (0, 1,1) (0,1,1)s while the savings deposits are an ARIMA (0, 2, 1) (0, 1,1)s , where S = 4 or 12, which indicates a model for quarterly or monthly data respectively.
Keywords
Time-Series; Nonstationary; Autoregressive Processes; Moving Average Processes; Seasonality; Hypothesis Testing; Forecasting
Statistics
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