Statistical Factor Model
Fit a statistical factor model using Principal Component Analysis (PCA)
statistical.factor.model(R, k = 1, ...)
R |
xts of asset returns |
k |
number of factors to use |
... |
additional arguments passed to |
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.
#'
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.
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