  Shrunk sample covariance matrix is a factor model of a special form combining
some (typically, style) risk factor(s) and principal components with a
(block-)diagonal factor covariance matrix. As such, shrinkage, which
essentially inherits out-of-sample instabilities of the sample covariance
matrix, is not an alternative to multifactor risk models but one out of myriad
possible regularization schemes. We give an example of a scheme designed to be
less prone to said instabilities. We contextualize this within multifactor
models.
