upside frequency of the return distribution

To calculate Upside Frequency, we take the subset of returns that are more than the target (or Minimum Acceptable Returns (MAR)) returns and divide the length of this subset by the total number of returns.

UpsideFrequency(R, MAR = 0, ...)

Arguments

R

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

Minimum Acceptable Return, in the same periodicity as your returns
…

any other passthru parameters

Details

$$ UpsideFrequency(R , MAR) = \sum^{n}_{t=1}\frac{max[(R_{t} - MAR), 0]}{R_{t}*n}$$

where \(n\) is the number of observations of the entire series

References

Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.94

Examples

data(portfolio_bacon)
MAR = 0.005
print(UpsideFrequency(portfolio_bacon[,1], MAR)) #expected 0.542
#> [1] 0.5416667

data(managers)
print(UpsideFrequency(managers['1996']))
#>                             HAM1 HAM2      HAM3      HAM4 HAM5 HAM6 EDHEC LS EQ
#> Upside Frequency (MAR = 0%) 0.75  0.8 0.8333333 0.6666667  NaN  NaN         NaN
#>                              SP500 TR US 10Y TR US 3m TR
#> Upside Frequency (MAR = 0%) 0.8333333 0.4166667        1
print(UpsideFrequency(managers['1996',1])) #expected 0.75
#> [1] 0.75