Description Usage Arguments Details Author(s) References Examples
The regression epsilon is an error term measuring the vertical distance between the return predicted by the equation and the real result.
1 | CAPM.epsilon(Ra, Rb, Rf = 0, ...)
|
Ra |
an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns |
Rb |
return vector of the benchmark asset |
Rf |
risk free rate, in same period as your returns |
... |
any other passthru parameters |
epsilon_r = r_p - alpha_r - beta_r * b
where α_r is the regression alpha, β_r is the regression beta, r_p is the portfolio return and b is the benchmark return
Matthieu Lestel
Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.71
1 2 3 4 5 6 | data(portfolio_bacon)
print(SFM.epsilon(portfolio_bacon[,1], portfolio_bacon[,2])) #expected -0.013
data(managers)
print(SFM.epsilon(managers['1996',1], managers['1996',8]))
print(SFM.epsilon(managers['1996',1:5], managers['1996',8]))
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