Analysis of the influence networks among stock indexes by using Transfer Entropy

Abstract

Recent research has explored the proper method to analyse the relationships in financial markets for risk management, In this paper, we apply transfer entropy to construct a stationary network which represents the information propagation between stocks. This network can differ significantly from other static networks, such as correlations network and minimal spanning tree network, because it can include the direction information. We demonstrate that this method reveals meaningful hidden relations of cause and effect between stocks.