New answers tagged


Alpha is a risk measurement & is not equal to excess return because of the beta. See link :


I'm guessing you are regressing excess returns $R_i$ on asset $i$ (so returns $r_i$ minus the risk-free rate $r_f$). Then, for market excess returns $R_M=r_M-r_f$, we have: $$ \begin{align} R_i &= r_i - r_f = \alpha_i + \beta_i R_M + \epsilon_i \quad \text{or} \\ r_i &= r_f + \alpha_i + \beta_i R_M + \epsilon_i, \\ \implies \bar{R}_i &= \hat\...


You should use 252 trading days. To annualize returns, multiply the average daily return by 252. To annualize volatility, multiply the daily volatility by sqrt(252). You can also use log daily returns if you prefer.


ann_return = df["Rate of Return"].mean()*12 ann_vol = df["Rate of Return"].std()*np.sqrt(12) You could also use log returns if desired.

Top 50 recent answers are included