error of the alpha estimate is 1.02. The estimate of alpha is far less than twice its standard error. Consequently, we cannot reject the hypothesis that the true alpha is zero.   CONCEPT C H E C K ☞ QUESTION 5 What was GMs CAPM alpha per month during the period covered by the Merrill Lynch regres- sion if during this period the average monthly rate of return on T-bills was .6%?     Most importantly, these alpha estimates are ex post (after the fact) measures. They do not mean that anyone could have forecasted these alpha values ex ante (before the fact). In fact, the name of the game in security analysis is to forecast alpha values ahead of time. A well-constructed portfolio that includes long positions in future positive-alpha stocks and short positions in future negative-alpha stocks will outperform the market index. The key term here is "well constructed," meaning that the portfolio has to balance concentration on high alpha stocks with the need for risk-reducing diversification. The beta and residual variance estimates from the index model regression make it possible to achieve this goal. (We examine this technique in more detail in Part VII on active portfo- lio management.) Note that GMs RESID STD DEV-N is 7.78% per month and its R 2 is .11. This tells us that 2 (e) 7.782 60.53 and, because R 2 1 2(e)/ 2, we can solve for the estimate of GMs total standard deviation by rearranging equation 10.13 as follows:   2 (e) 1/2   60.53 1/2   1 R2 a .89 b 8.25% per month   This is GMs monthly standard deviation for the sample period. Therefore, the annualized standard deviation for that period was 8.25 12 28.58%. Finally, the last column shows the number of observations, which is 60 months, unless the stock is newly listed and fewer observations are available.     Predicting Betas   We saw in the previous section that betas estimated from past data may not be the best es- timates of future betas: Betas seem to drift toward 1 over time. This suggests that we might want a forecasting model for beta. One simple approach would be to collect data on beta in different periods and