def shrunk_covariance(self, delta=<NUM_LIT>):
self.delta = delta<EOL>N = self.S.shape[<NUM_LIT:1>]<EOL>mu = np.trace(self.S) / N<EOL>F = np.identity(N) * mu<EOL>shrunk_cov = delta * F + (<NUM_LIT:1> - delta) * self.S<EOL>return self.format_and_annualise(shrunk_cov)<EOL>
Shrink a sample covariance matrix to the identity matrix (scaled by the average
sample variance). This method does not estimate an optimal shrinkage parameter,
it requires manual input.

:param delta: shrinkage parameter, defaults to 0.2.
:type delta: float, optional
:return: shrunk sample covariance matrix
:rtype: np.ndarray