Correlation network analysis for multi-dimensional data in stocks market

Abstract

This paper shows how the concept of vector correlation can appropriately measure the similarity among multivariate time series in stocks network. The motivation of this paper is (i) to apply the RV coefficient to define the network among stocks where each of them is represented by a multivariate time series; (ii) to analyze that network in terms of topological structure of the stocks of all minimum spanning trees, and (iii) to compare the network topology between univariate correlation based on r and multivariate correlation network based on RV coefficient.