We are working on Categorical, Macro, Grid.
The Macro factor is tricky. We re-read the Gu paper and it seems that they are multiplying every feature by the normalized macro factor. It's also not clear what normalization they are using. What we are doing now, treating macro factor like any other feature, is completely wrong (wish we never added macros to predefined features). If anyone has suggestions how to treat macros please let us know.
Ensemble models is just adding multiple AIFactors to a ranking system, no? Or do you mean testing ensemble models within a cross validation?
Not sure what this is "Ability to smooth the predictors to reduce turnover"
Thanks