Forecasting Lending Interest Rate and Deposit Interest Rate of Bangladesh Using Autoregressive Integrated Moving Average (ARIMA) Model

Abstract

The purpose of this paper is to predict the lending interest rate and deposit interest rate of Bangladesh using the Autoregressive Integrated Moving Average (ARIMA) model by Box Jenkins. It has been found that ARIMA (1, 0, 1) model is appropriate in predicting both the lending and deposit interest rates from 2022 to 2026 using the data presented in the World Bank Open Data from 1976 to 2021. To test the goodness of fit, AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion) index values have been calculated for six ARIMA models. Besides, Dickey-Fuller unit root test and Correlogram test have also been conducted for diagnostic tests.

Keywords

• Lending interest rate
• Deposit interest rate
• Stationary
• Box –Jenkins approach
• ARIMA (p,d,q) model
• Forecasting