COMPARATIVE ANALYSIS OF AUTOREGRESSIVE INTEGRATED MOVING AVERAGES MODEL ON RESAMPLED AND NON-RESAMPLED INFLATION TIME SERIES DATA FOR FORECASTING.

The study compared the efficiency of establishing of variance obtained from Autoregressive Integrated Moving Averages (ARIMA) model for resampled inflation time series and actual inflation time series. Using the Akaike Information Criterion (AIC), most efficient forecast was obtained. Results shows that the models fit on resampled inflation series produced higher AICs than the actual data. Thus the models fit on the actual data are considered better for forecast.