Abstract
In this study application of ARIMA and Artificial Neural Networks for Forecasting Bank Deposits Rate is investigated. As it's observed nowadays, banking industry is faced with great competition. The number of banks and use of new tools especially electronic banking and development of Islamic banking have maximized this competition and turned intelligent management of banks into a critical issue. Foundation of banks is based on attracting deposits; hence, forecasting the deposits has a great importance for banks. This study seeks to forecast the bank deposits. To do this, we have used the ARIMA methods with emphasis on the Box-Jenkins method as well as the Artificial Neural Network. The monthly data of different branches was used in this study for an eight-year period. This study examined the hypothesis that neural networks are more accurate than ARIMA models in forecasting the bank deposits. Research results indicate that although both models have a high capacity to forecast the variables, generally the neural network models present better results and it is better to use this method for forecasting. The neural network method has a relative advantage as R 2 is 16% in ARIMA Method and 99% in Neural network Method. Also RMSE is 170985 and 176960 for ARIMA Method and Neural network Method respectively.
Highlights
In today economy, the financial institutions and organizations have a position under which no economy can survive without these institutions
Autoregressive Integrated Moving Average process (ARIMA): If a time series becomes stationary after d time of first order difference and it is modeled by the process ARMA(p, q), the main time series is the time series of Autoregressive Integrated Moving Average Process ARIMA(, ݀, )ݍin which p is the number of autoregressive terms, d: the number of firstorder differencing to become stationary time series; and q: is the number of moving average terms
The first order difference of total deposits is displayed by X* and the first order difference of longterm investment deposits displayed as X*1
Summary
The financial institutions and organizations have a position under which no economy can survive without these institutions. Financial organizations are increasing in general and the number of banks is enhancing in particular and the competition among them is being more intense. This competition will lead to the use of new management methods and use of appropriate tools. Basis and continuation of bank activities is based on the attraction of financial resources and the life of a bank is based on the increased attraction of resources and their optimal management. Given the random nature of bank activities in attracting the deposits, forecasting this issue is among the important issues for banks. The rate of attracting the deposits is among these forecasts
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