Complex Networks with Applicability to the Structure and Dynamics of Stock Market Evolution

Abstract

The speed at which economic phenomena of all kinds evolve at international level leads to many imperfections and causes major economic, social, and political issues. Our study enables the use of complex networks in a field that is often difficult for the general public to grasp, namely, the stock market. By using graph theory, which we applied to stock indices, we were able to follow the overall evolution of those markets. The manner in which we applied certain techniques and methods to selected indices enabled us to have a novel approach, by obtaining shapes with spatial representations. These subgraphs and complete graphs thus determined allow highlighting of certain aspects that can influence certain capital markets. Refining some derivative financial analysis instruments makes it possible to model some economic process networks.