Given two square matrices $A$ and $B$. There are quite some results on the distance between the eigenvalues, e.g., 

$$
| \lambda_A - \lambda_B | \leq \| A - B \|_F,
$$
where $A$ and $B$ are Hermitian (see [here for more][1]). I am looking for similar results for the argument of the eigenvalues, for example  
$$
| arg(\lambda_A) - arg(\lambda_B) | \leq \| A - B \|_?
$$
One simple instance I have found: if invertible $A$ is normal, given the polar decomposition $A = UP$, then $| arg(\lambda_A) - arg(\lambda_U) | = 0$. Can this result be extended in terms of perturbation?  



  [1]: http://www.netlib.org/lapack/lawnspdf/lawn84.pdf