CAPM goodness of fit I want to test the CAPM. I have collected monthly data from 1-9-2012 to 1-9-2017. I have data from the return of Standard&amp;Poor's 500 and data from various US companies. The beta's seem right, but my goodness of fit ($R^2$) are low: Ameren 0.0614, Apple 0.2456. My question is: Can this be right? If you're testing the CAPM or am I doing something wrong. I used the CAPM regression $R_{i,t}-R_{f,t}=\alpha_i+\beta_i(R_{M,t}-R_{f,t})+e_i$.
$\beta$ is the measure of the sensitivity of stock returns to market returns. This has nothing to do with the value of $R^2$.

Your results appear to be fine, you can get significant beta estimates but low $R^2$. Why? 

As measured by $R^2$, 24.56% of variation in Apple returns is accounted for by the variation in the market index, $S$&amp;$P 500$. Clearly, there must be other factors that determine the remaining 75.44$% of variation in the Apple returns. Other factors that you could include in the model are copmany size and market to book value (Fama and French Three-Factor Model). By including these omitted variables in your new model, you may achieve higher r-squared value.