bootstrap procedure that leads to a robust estimate of the variance-covariance matrix. Monte Carlo results reveal that these …

two-multiple convolution of ковариантного tensor of the covariance matrix and kontravariant vector of weights. By means of … reduction of covariance matrix to the diagonal form, the problem by definition of optimum structure of a portfolio is solved …

This paper proposes a conjugate Bayesian regression model to estimate the covariance matrix of a large number of … delivers a fully-automated covariance matrix estimator with beliefs that become diffuse as the sample grows relative to the … dimension of the problem. In application, this Stein-optimal posterior covariance matrix performs well in a large set of …

The likelihood ratio (LR) for testing if the covariance matrix of the observation matrix X is R has some invariance … properties that can be exploited for covariance matrix estimation purposes. More precisely, it was shown in Abramovich et al …. (2004, 2007, 2007) that, in the Gaussian case, LR(R0|X), where R0 stands for the true covariance matrix of the observations …

This paper deals with the problem of estimating the normal covariance matrix relative to the Stein loss. The main …