code: def ols_covariance(self):
                   
  
          Y = np.array([reg[self.lags:reg.shape[0]] for reg in self.data])        
          return (1.0/(Y[0].shape[0]))*np.dot(self.residuals(Y),np.transpose(self.residuals(Y)))
docs: Creates OLS estimate of the covariance matrix
  
          Returns
          ----------
          The OLS estimate of the covariance matrix