Title（标题）：On estimation of the population spectrum from large dimensional

covariance matrices

Speaker（汇报人）：Prof. Jianfeng Yao, The University of Hong Kong

Time（功夫）：2012年5月17日（周四）下午02:00-3:00

Place（地址）：拉斯维加斯9888新楼217教室

Abstract（提要）：For large-dimensional data, sample covariance matrices significantly deviate from the population covariance matrix. For various inference problem, it is then crucial to recover population characteristics, e.g. distribution of eigenvalues of the population covariance matrix from the sample covariance matrices. First we will give a review of existing methods for estimation of this distribution. Then recent advances on this topic using contour-integral based methods or extended Stieldjes transform will be presented. In particular advantages and weakness of these methods will be discussed and compared.In the context of time series, these methods can be applied to series of returns that are widely accepted as uncorrelated in time. The discussed methods are therefore intended to a analysis of the correlation structure within different stock prices.