I'm conducting an economic forecast based on an ARIMA time series model with multiple independent variables. I'm using a daily time series data that contains about 2 years of daily data inputs for a sum of 8 different regressors.
My ARIMA fit is so good so far but I'm wondering why the external regressors are not of a great effect to the predicted values. In my model the predicted values and $R^2$ are only slightly affected regardless of whether I include the external regressors or not.
In both cases the number of observations is equal and the adjusted R2=0.97 (Predicted value is not of a great change).
Could anybody help me with the significance of this phenomenon?
Thanks Mr. Richard Hardy for your help. It is highly appreciated