Set portfolio moments for use by lower level optimization functions. Currently three methods for setting the moments are available
set.portfolio.moments(R, portfolio, momentargs = NULL, method = c("sample",
"boudt", "black_litterman", "meucci"), ...)an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
an object of type "portfolio" specifying the constraints and objectives for the optimization, see portfolio.spec
list containing arguments to be passed down to lower level functions, default NULL
the method used to estimate portfolio moments. Valid choices include "sample", "boudt", and "black_litterman".
any other passthru parameters
sample: sample estimates are used for the moments
boudt: estimate the second, third, and fourth moments using a
statistical factor model based on the work of Kris Boudt.
See statistical.factor.model
black_litterman: estimate the first and second moments using the
Black Litterman Formula. See black.litterman.