statistical.factor.model {PortfolioAnalytics} | R Documentation |
Statistical Factor Model
Description
Fit a statistical factor model using Principal Component Analysis (PCA)
Usage
statistical.factor.model(R, k = 1, ...)
Arguments
R |
xts of asset returns |
k |
number of factors to use |
... |
additional arguments passed to |
Details
The statistical factor model is fitted using prcomp
. The factor
loadings, factor realizations, and residuals are computed and returned
given the number of factors used for the model.
Value
#'
factor_loadings N x k matrix of factor loadings (i.e. betas)
factor_realizations m x k matrix of factor realizations
residuals m x N matrix of model residuals representing idiosyncratic risk factors
Where N is the number of assets, k is the number of factors, and m is the number of observations.
[Package PortfolioAnalytics version 1.1.0 Index]