Suppose I have a Time Series Model (assume ARIMA) and use it to make one-step ahead prediction.
If I acquire a new data point, (for example I was originally using the first 100 days to fit an Arima model to predict 101st day, now I observe the data of 101st day and want to use 101 days of data to predict the 102nd day), Should I?
Refit everything, including mega parameters $p,d,q$?
Let $p,d,q$ remain what it is, but refit the coefficient of the ARIMA model?
Or if there's other protocol when we face this kind of problem?
I am relatively new to this area so any advice, insights and suggestions will be appreciated. Thanks.