Alpha is a risk-adjusted measure of active return on an investment.
The FF 3 factor model is emerging 2 classes of stock with CAPM to reflect a portfolio's theory.
r - Rf = beta3 x ( Km - Rf ) + bs x SMB + bv x HML + alpha
Alpha Coefficient can show that in an efficient market, the expected value of the alpha coefficient is zero. Therefore the alpha coefficient indicates how an investment has performed after accounting for the risk it involved:
Alpha_i < 0 : the investment has earned too little for its risk (or, was too risky for the return)
Alpha_i = 0 : the investment has earned a return adequate for the risk taken
Alpha_i > 0 : the investment has a return in excess of the reward for the assumed risk
Absolutely. Take the case of a portfolio. The measurement of alpha with CAPM assumes that a portfolio is (1) passive and (2) similar in style and value as the "market." In this case, a significant negative or positive alpha can be a distortion. For example, if (1) your portfolio is more value-oriented than the "market" and (2) value stocks have overperformed growth stocks during the period of evaluation, your portfolio alpha is overestimated. Now, if you orthogonalize alpha for value and size biases, then your measurement of "excess return" is more refined. Momentum (Carhart) and market timing are also factors can be added. In fact, professional (commercial) factor models like MSCI BARRA use up to 8 or 10 risk factor groups comprised of 100s of risk macro components (liquidity, confidence, volatility, trading activity, etc.).
Alpha will never be zero, it cannot be zero, there will always be excess returns / negative alpha returns and the rest will be explained by correlations and the three Betas as shown in various Fama French model computations across 100 markets
http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html
Of course the error of alphas is not really attributable to the Risk free rate and has not been explained in belief expectations either
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