I am building time series models using SARIMAX from Statsmodels (Python).
The independent variables in my models include 3 to 5 exogenous variables that are other than the target variable I am trying to predict.
I am finding that there is some value in using Box-Cox to transform my target (i.e. independent) variable.
In these cases, should I also be applying the same Box-Cox transformation to my exogenous variables?
(I believe the answer is no.)