# Does forecasting with ARIMA lose non-stationary components?

Suppose I have a time series $$Y$$. I have read that an ARIMA model consists as an ARMA model of a stationarized version of $$Y$$.

If I try to predict $$n$$ ticks ahead with an ARIMA forecast model (with $$n$$ big), would I loose any non-stationary component of $$Y$$ like trend or seasonality ?

• No you don't, because part of the ARIMA process is reverse transforming the forecasts after they are generated. – Skander H. Dec 6 '18 at 16:55