Skewness-Kurtosis ratio is the division of Skewness by Kurtosis.

SkewnessKurtosisRatio(R, ...)

Arguments

R

an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns

any other passthru parameters

Details

It is used in conjunction with the Sharpe ratio to rank portfolios. The higher the rate the better. $$ SkewnessKurtosisRatio(R , MAR) = \frac{S}{K}$$

where \(S\) is the skewness and \(K\) is the Kurtosis

References

Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.100

Examples

data(portfolio_bacon) print(SkewnessKurtosisRatio(portfolio_bacon[,1])) #expected -0.034
#> [1] -0.03394204
data(managers) print(SkewnessKurtosisRatio(managers['1996']))
#> HAM1 HAM2 HAM3 HAM4 HAM5 HAM6 #> SkewnessKurtosisRatio -0.1364114 0.1279073 -0.3322627 -0.0264609 NA NA #> EDHEC LS EQ SP500 TR US 10Y TR US 3m TR #> SkewnessKurtosisRatio NA -0.03981589 -0.01634447 -0.2626715
print(SkewnessKurtosisRatio(managers['1996',1]))
#> [1] -0.1364114