I just conducted a Fama-Macbeth regression where in the first step I calculated a time-series regression for each individual stock to get three betas (for mkt-rf, smb, hml) for each stock. Then I ran a cross-sectional regression with the returns of all companies at each timepoint as my dependent variable and the all the estimated betas of all companies as the independent variables. This gave me a time-series of the different risk premia of which I took a simple average.
Unfortunately, the results are very weird from my perspective. As I cannot find a mistake in my regression, I'd like to ask if anyone of you can somehow explain the results:
The risk premium of Mkt-Rf is -0.11% per month (but not statistically significant), SMB is 0,62% (significant) and HML -0,14% (not significant). Additionally I get a (in my opinion very high) alpha of 1.05% which is statistically significant.
While this is already very strange as I expected HML and especially Mkt-Rf to be positive, at least they're not significant.
But even worse, I tried to double check my results.
I checked four subperiods as e.g. the Value-Premium/HML wasn't performing since the financial crisis 2007. Not even the Pre-crisis era from 2000-2007 in which HML performed really well.
Instead of the three-factor model I caluclated CAPM and a two-factor model just with SMB. Against all my expectations the Alpha was lower in the One-factor-modell than in the other two although two factors where added which should increase the explanatory power and decrease the alpha.
Has anyone of you a logical explanation for the results? Otherwise I probably should check my calculcations again.