Suppose I have only 1 variable (data on export, monthly, non-seasonally adjusted) from Jan 1960 till Mar 2019. My task is to obtain forecasts of this series for the coming year (i.e. Apr 2019 - Mar 2020), using the data on export.
I have plotted the raw data, to look for any potential trend and stationarity. I have run the Augmented Dickey-Fuller test on the raw data, and at 5% significance level, we rejects the null hypothesis, in favor of stationarity. In this case, can I assume that the time series is stationary? Or do I have to do more to determine?
Also, I am wondering how I can fit a model for forecasting. Do I simply throw it into
R? Another question is, how should I determine whether I should transform my data?
I am a new forecaster here, so any thoughts will be appreciated on how I should go about to do this.