The t stat for the beta estimate is statistically significant.

It is 9.44851.

So the beta estimate is statistically significant, different than 0.

But the alpha estimate is not.

Since the t stat associated is only 0.10.

Which is of course less than the 1.96 variable.

So in the previous example we looked at the CAPM alpha.

We used the single factor index model.

Now it's fairly easy to generalize this to a multi-factor model

such as the Fama-French three factor model.

Right?

You would simply be estimating a multivariate regression.

Instead of a regression with one single independent variable.

So in this case, what would the model look like?

Well, it will look something like this.

Your portfolio takes this return on your

portfolio = alpha + the market beta

times their excess return on the market,

plus now you're going to have other factors.

The size beta times the size factor

plus the value beta times the value

factor plus the epsilon.

And again you would be estimating this

model to compute the three factor alpha.

Now okay, remember, What the alpha represents.

It is the excess return that is being generated above and

beyond what is accounted for risk.

So when we're estimating the Fama-French three factor model.

We're accounting for presumably all the different risk factors.

So, the alpha is really

the maximum amount that you should be willing to compensate a portfolio manager.

For their active management of the portfolio.