Total risk of the return distribution

The square of total risk is the sum of the square of systematic risk and the square of specific risk. Specific risk is the standard deviation of the error term in the regression equation. Both terms are annualized to calculate total risk.

TotalRisk(Ra, Rb, Rf = 0, ...)

Arguments

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

Details

$$Total Risk = \sqrt{Systematic Risk^2 + Specific Risk^2}$$

References

Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.75

Author

Matthieu Lestel

Examples

data(portfolio_bacon)
print(TotalRisk(portfolio_bacon[,1], portfolio_bacon[,2])) #expected 0.0134
#> [1] 0.136828

data(managers)
print(TotalRisk(managers['1996',1], managers['1996',8]))
#> [1] 0.05627721
print(TotalRisk(managers['1996',1:5], managers['1996',8]))
#>                     HAM1 HAM2      HAM3      HAM4 HAM5
#> Total Risk =  0.05627721   NA 0.1079938 0.1099375   NA