Suppose you have two models, model A and model B, and let these models forecast 10 time series over a horizon of 12 periods. That is, suppose the time series contain monthly data and your forecasting horizon is 1 year.
Can I then statistically test whether model A is 'better' than model B over all the time series? I know that the Diebold-Mariano test can be used to see if the forecasts of model A and model B are statistically different for one specific time series. However, I don't think that this method can be directly generalized to multiple time series, correct?