Geometric optimisation algorithms are developed that efficiently find the nearest low-rank correlation matrix. We show … nearest low-rank correlation matrix occurs as part of the calibration of multi-factor interest rate market models to … correlation. Keywords: geometric optimisation, correlation matrix, Rank, LIBOR market model …

In this paper a Canonical Correlation Analysis (CCA) is used to test the hypothesis r = r0 against the alternative r …

The Gaussian rank correlation equals the usual correlation coefficient computed from the normal scores of the data … correlation matrix based on the Gaussian rank correlation is always positive semidefinite, and very easy to compute, also in high … the popular Kendall and Spearman correlation measures. In the empirical application, we show how it can be used for …

Spearman's rank correlation is a robust alternative for the standard correlation coefficient. By using ranks instead of … on this rank correlation measure for estimating covariance matrices and their inverses. The resulting estimator is robust … is therefore said to be sparse. Instead of Spearman's rank correlation, one can use the Quadrant correlation or Gaussian …