# Tag Info

In the second pass, the independent variables are the first pass estimated betas. That is, you estimate $\hat{\beta_i}$ in time series for every stock i $$r_{i,t} - r_{f,t} = \alpha_i + \beta_i(r_{M,t}-r_{f,t}) + \epsilon_t$$ and then you estimate risk premia $\hat{\lambda}$ according to the following regression: \overline{r_{i,t} - r_{f,t}} = a_0 + ...