Question #264328
What is a possible drawback of using R2 for comparing different models with the same dependent variable and different number of explanatory variables? Why using adjusted R2 for model evaluation may be better?
Expert's answer
R-squared does not measure goodness of fit. R-squared does not measure predictive error. R-squared does not allow you to compare models using transformed responses. R-squared does not measure how one variable explains another.
Many investors prefer adjusted R-squared because adjusted R-squared can provide a more precise view of the correlation by also taking into account how many independent variables are added to a particular model against which the stock index is measured.
