Net selectivity of the return distribution

Net selectivity is the remaining selectivity after deducting the amount of return require to justify not being fully diversified

Usage

NetSelectivity(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

If net selectivity is negative the portfolio manager has not justified the loss of diversification

$$Net selectivity = \alpha - d$$

where \(\alpha\) is the selectivity and \(d\) is the diversification

References

Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.78

Author

Matthieu Lestel

Examples

data(portfolio_bacon)
print(NetSelectivity(portfolio_bacon[,1], portfolio_bacon[,2])) #expected -0.017
#>                              portfolio.monthly.return....
#> portfolio.monthly.return....                   -0.0178912

data(managers)
print(NetSelectivity(managers['1996',1], managers['1996',8]))
#>            HAM1
#> HAM1 0.01333906
print(NetSelectivity(managers['1996',1:5], managers['1996',8]))
#>                                       HAM1 HAM2      HAM3        HAM4 HAM5
#> Net Selectivity (Risk free = 0) 0.01333906   NA 0.1745397 -0.03249043   NA