Análise de séries temporais do mercado financeiro utilizando teoria de redes complexas

Abstract

In spite of being an area commonly studied by economists and mathematicians, the analysis of economic systems has attracted a growing number of physicists. Consequently, complex system and network science tools have been proven to be extremely useful in the modeling of financial markets. In particular, concepts such as correlation distance and minimal spanning tree (MST) have been widely used in the literature to study the dynamics of financial markets, through similarities of measures, risk analysis and behaviour in periods of financial crises. In this work, we use financial market data composed of indices of several countries and regions, currencies, commodities, government bonds, among others. We analyse how different financial groups are related by taking their correlation into account. In addition to that, we use the correlations between assets to create the MST and study its network properties.