It is well established that the standard measure of correlation (Pearson’s product-moment) is very sensitive to … correlation measures have been proposed. We do not consider estimators which require trimming (discarding) of some arbitrary … measure of correlation which can be recommended to practitioners alongside the classic Pearson and Spearman measures. The well …

, the winner would most likely be the correlation coefficient with a significant difference from its first competitor. In …. Therefore, we search for robust correlation coefficients to nonnormality and outliers that could be applied to all applications … and detect influenced or hidden correlations not recognized by the most popular correlation coefficients. We introduce a …

Canonical correlation analysis (CCA) is a multivariate statistical method which describes the associations between two … correlation. This paper discusses a method for Robust Sparse CCA. Sparse estimation produces canonical vectors with some of their …

these forecasts. In this paper we analyse these effects on the context of dynamic conditional correlation (DCC) models when … for return, volatilities, conditional correlation and VaR that is robust to outliers. The results are illustrated with …

We introduce the Gerber statistic, a robust measure of correlation. The statistic extends Kendall's Tau by counting the … standard Pearson correlation that is sensitive to outliers or the Spearman correlation that relies on ranking observations …