I have two different (regression) models spitting out predictions on a daily basis for the same dependent variable. My intention is to assign weights to those two predictions and calculate a weighted average. To this end, I have developed a simple system where the MSEs of the models are calculated and used as weights everyday. As a result, the higher the MSE a model has, the lower the weight it is assigned to the model. However, this is a very lame approach and I haven't observed any improvement compared to taking a simple average of the predictions. So what are the ways that I can use to assign weights to those predictions dynamically. That is, I want to update the weights everyday. From where should I start?
Note: I am aware that with ensemble models, I can get the weights automatically (i.e. H2O stacked ensemble). However, I am not allowed to retrain the predictions everyday. So applying an ensemble method and retrain it everyday is not applicable in my case.
Thanks in advance!