Description Usage Arguments Details Author(s) See Also Examples
calculates Standard Deviation for univariate and multivariate series, also calculates component contribution to standard deviation of a portfolio
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R 
a vector, matrix, data frame, timeSeries or zoo object of asset returns 
... 
any other passthru parameters 
clean 
method for data cleaning through

portfolio_method 
one of "single","component" defining whether to do univariate/multivariate or component calc, see Details. 
weights 
portfolio weighting vector, default NULL, see Details 
mu 
If univariate, mu is the mean of the series. Otherwise mu is the vector of means of the return series , default NULL, , see Details 
sigma 
If univariate, sigma is the variance of the series. Otherwise sigma is the covariance matrix of the return series , default NULL, see Details 
use 
an optional character string giving a method
for computing covariances in the presence of missing
values. This must be (an abbreviation of) one of the
strings 
method 
a character string indicating which
correlation coefficient (or covariance) is to be
computed. One of 
TODO add more details
This wrapper function provides fast matrix calculations for univariate, multivariate, and component contributions to Standard Deviation.
It is likely that the only one that requires much description is the component decomposition. This provides a weighted decomposition of the contribution each portfolio element makes to the univariate standard deviation of the whole portfolio.
Formally, this is the partial derivative of each univariate standard deviation with respect to the weights.
As with VaR
, this contribution is presented
in two forms, both a scalar form that adds up to the
univariate standard deviation of the portfolio, and a
percentage contribution, which adds up to 100
as with any contribution calculation, contribution can be
negative. This indicates that the asset in question is a
diversified to the overall standard deviation of the
portfolio, and increasing its weight in relation to the
rest of the portfolio would decrease the overall portfolio
standard deviation.
Brian G. Peterson and Kris Boudt
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