Hierarchical Structure in Financial Markets

TL;DR

This paper uncovers a hierarchical topological structure in financial markets by analyzing stock correlations, revealing an economic taxonomy that helps understand common factors influencing stock price movements.

Contribution

It introduces a novel method of constructing a hierarchical graph from stock correlations to identify economic groupings and underlying factors.

Findings

Identification of a meaningful economic taxonomy among stocks

Hierarchical ultrametric space reveals common economic factors

Graph-based approach enhances understanding of market structure

Abstract

I find a topological arrangement of stocks traded in a financial market which has associated a meaningful economic taxonomy. The topological space is a graph connecting the stocks of the portfolio analyzed. The graph is obtained starting from the matrix of correlation coefficient computed between all pairs of stocks of the portfolio by considering the synchronous time evolution of the difference of the logarithm of daily stock price. The hierarchical tree of the subdominant ultrametric space associated with the graph provides information useful to investigate the number and nature of the common economic factors affecting the time evolution of logarithm of price of well defined groups of stocks.