Description Usage Arguments Details Author(s) References Examples
Adjusted Sharpe ratio was introduced by Pezier and White (2006) to adjusts for skewness and kurtosis by incorporating a penalty factor for negative skewness and excess kurtosis.
1  | AdjustedSharpeRatio(R, Rf = 0, ...)
 | 
R | 
 an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns  | 
Rf | 
 the risk free rate  | 
... | 
 any other passthru parameters  | 
Adjusted Sharpe ratio = SR x [1 + (S/6) x SR - ((K-3) / 24) x SR^2]
where SR is the sharpe ratio with data annualized, S is the skewness and K is the kurtosis
Matthieu Lestel
Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.99
1 2 3 4 5 6  | data(portfolio_bacon)
print(AdjustedSharpeRatio(portfolio_bacon[,1])) #expected 0.81
data(managers)
print(AdjustedSharpeRatio(managers['1996']))
print(AdjustedSharpeRatio(managers['1996',1])) 
 | 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.