A Hybrid Model Based on ARIMA and Artificial Neural Network to Forecast Consumer Price Index: The Case of Vietnam

While the Autoregressive Integrated Moving Average (ARIMA) model has been dominantly used to capture a linear component of time series data in the field of economic forecast for years, the Artificial Neural Networks (ANNs) increasingly are applying to explore tough challenge due to an existence of both linear and nonlinear patterns in a certain time series dataset. Regarding the time series forecasting, most studies have applied only ARIMA model or ANNs to produce multiple-step prediction with an insufficiently reasonable accuracy. That’s why this paper suggests a hybrid model with the advantages of either ARIMA or ANNs to analyze the linear and nonlinear relationships in Vietnam CPI time series from January 1995 to July 2022. The result shows that an effectiveness in the multiple-step prediction of the hybrid model is more precise in comparison with ARIMA model and ANNs.