Dear all,
This is a purely statistical question, and has nothing to do with the programming language implementiation in Stata, as I've already managed to do it.
I need to conduct the Fama-MacBeth (FM) procedure for my thesis to test the ability of the Fama-French (2015) and Carhart (1997) six-factor model to predict future expected returns. In univariate regressions of expected excess returns on the market excess return, both average intercept and slope coefficients are statistically significant at the 1% level. When augmenting the regression model with the FF (2015) and Carhart (1997) factors, all variables are insignificant, but the intercept coefficient remains highly significant at the 1% level.
Basically, what I need to know is whether the CAPM holds. I know that, in a cross-sectional OLS setup, the intercept has to be statistically irrelevant and close to zero (α = 0), while the coefficient on the market excess return should be statistically significant and close to one (β = 1). However, I'm a bit confused as to how FM regression results are supposed to be interpreted.
Two questions:
This is a purely statistical question, and has nothing to do with the programming language implementiation in Stata, as I've already managed to do it.
I need to conduct the Fama-MacBeth (FM) procedure for my thesis to test the ability of the Fama-French (2015) and Carhart (1997) six-factor model to predict future expected returns. In univariate regressions of expected excess returns on the market excess return, both average intercept and slope coefficients are statistically significant at the 1% level. When augmenting the regression model with the FF (2015) and Carhart (1997) factors, all variables are insignificant, but the intercept coefficient remains highly significant at the 1% level.
Basically, what I need to know is whether the CAPM holds. I know that, in a cross-sectional OLS setup, the intercept has to be statistically irrelevant and close to zero (α = 0), while the coefficient on the market excess return should be statistically significant and close to one (β = 1). However, I'm a bit confused as to how FM regression results are supposed to be interpreted.
Two questions:
- What does the significant intercept in the CAPM regression exactly mean in the FM regression framework? Does it imply that the CAPM fails?
- What is the reason for beta to be significant in the simple regression, but insignificant in the multivariate specification?
