  We summarize properties of the spatial sign covariance matrix and especially
look at the relationship between its eigenvalues and those of the shape matrix
of an elliptical distribution. The explicit relationship known in the bivariate
case was used to construct the spatial sign correlation coefficient, which is a
non-parametric and robust estimator for the correlation coefficient within the
elliptical model. We consider a multivariate generalization, which we call the
multivariate spatial sign correlation matrix.
