Once we have built the regression model, we need to generate scores for a holdout sample. The holdout sample contains one month of observed data. At times, when building the model, we over fit the data. It is always a good idea to have a holdout sample on which the model can be fitted. There isn't anything better than using the observed values to see how well the predictions were made. The holdout sample shouldn't be too short or too future looking when compared to what has been built into the model.
We cannot expect the model that we have built for daily stock prices using almost three years of data to help us predict three years ahead. Also, using our model to predict just one day ahead and using that as a holdout ...
