I have a seasonally decomposed data set. The data set has strong seasonality.

Now I am trying to fit the 'seasonal part' of dataset into ARIMA model and tried to forecast (with SPSS).

The problem is, I get exactly same values in forecasts as that of actual values. So, MAPE is coming to be 0.000

Is this obvious to happen or am I doing something wrong?

P.S.

The data set is here: http://mihirsathe.com/mihir/STI/STI/drugs/index.html

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#### Best Answer

The seasonal factors are a set of constants repeating every 12 periods thus it is a deterministic series and then can't be modeled that's why the other responders are getting error messages. If you want to predict the seasonal component just extend the seasonal factors into the future . For example the sf of 227 = the seasonal factor for 215 = seasonal factor for 203 etc. thus the sf for 239 would the df for for 227 .

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