I have recently been refreshing my forecasting knowledge while working on some monthly forecasts at work and reading Rob Hyndman's book but the one place I am struggling is when to use an exponential smoothing model vs an ARIMA model. Is there a rule of thumb where you should use one methodology vs another?
Also, since you can't use AIC to compare the two do you just have to go by RMSE, MAE, etc?
Currently I am just building a few of each and comparing the error measures but I wasn't sure if there was a better approach to take.
Best Answer
Exponential Smoothing is in fact a subset of an ARIMA model. You don't want to assume a model, but rather build a customized model for the data. The ARIMA process let's you do that, but you need to also consider other items. You need to identify and adjust for outliers also. See more on Tsay's work with outliers here