Central Limit Theorem for traces of the resolvents of half-heavy tailed Sample Covariance matrices

Abstract

We consider the spectrum of the Sample Covariance matrix ${\mathbf{A}}_N:=\frac{{\mathbf{X}}_N{\mathbf{X}}_N^{\ast }}{N},$ where ${\mathbf{X}}_N$ is the $P\times N$ matrix with i.i.d. half-heavy tailed entries and $\frac{P}{N}\to y>0$ (the entries of the matrix have variance, but do not have the fourth moment). We derive the Central Limit Theorem for the Stieltjes transform of the matrix ${\mathbf{A}}_N$ and compute the covariance kernel. Apart from that, we derive the Central Limit Theorem for the Stieltjes transform of overlapping Sample Covariance matrices.