I am trying to do Fama Macbeth regression on some tradable factors using 5-year rolling window updated monthly. However, I am a little bit confused when calculating the final R-squared of the model. I am thinking about two ways to deal with it:
For each rolling window, I have one R-squared. To calculate the final R-squared of the model, I just take the average of all R-squared in each rolling window (just like the way we do with lambda) >> I get pretty good R-squared (around 70%-80%)
After extracting the final lambda for each factor, I use R-squared formula to calculate the final R-squared >> I get very bad R-squared (negative). In this case, I use dependent variables are average return of each portfolio, independent variables are obviously the betas, corresponding with factors and portfolios.
So how usually the final R-squared is calculated ?