Is your feature request related to a problem? Please describe.
It is somewhat unintuitive, that the model returns a standard error in the univariate case and but not in the multivariate case (due to using a tree based forecast in the multivariate case).

Describe the solution you'd like
Ideally the default forecaster should return the same output "format" (forecast and standard error) independent of the input data.
This would likely require changing the default forecaster for the multivariate case (A probabilistic tree based method like for example ngboost [https://github.com/stanfordmlgroup/ngboost] might be worth investigating for this.)

Describe alternatives you've considered
Given that the "ideal" solution is quite complex a lower effort alternative would be to make this behavior more clear in the description and documentation of the default forecast model.

Additional context
I think having a default model as an entry point to the forecasting case is a good idea. But the difference in forecast outputs for univariate and multivariate case somewhat defeats this purpose. Intuitively one would probably assume, that the default model has the same features in both cases.