I am learning about the ARIMA model and trying to implement it and had some questions. From my understanding, ARIMA forecasts better for short-term projections rather than long-term projections (is this true or false)? I am implementing the ARIMA to make a 6 month projection on a daily basis. Would I get better results if I predict one day, then retrain the model including that day, then predicting the next day, and then retraining, and so on?
EDIT: Thanks for the responses. Sorry if I wasn't being clear. I am using the ARIMAX model, and I have about 30 exogenous variables. I know what the actual values are for the endogenous variable, even for the 6 month projection period. I want to test how well my model performs on this 6 month period. So what I meant by retraining is that after I make a prediction for the next day using n samples, I would retrain on n+1 samples, where the new sample is using the actual value for the endogenous variable as opposed to the prediction.