Cluster formation and evolution in networks of financial market indices

Leonidas Junior Sandoval ()
Additional contact information
Leonidas Junior Sandoval: Insper, Instituto de Ensino e Pesquisa Rua Quatá

Algorithmic Finance, 2013, vol. 2, issue 1, 3-43

Abstract: Using data from world stock exchange indices prior to and during periods of global financial crises, clusters and networks of indices are built for asset graphs based on distance thresholds and diverse periods of time, so that it is then possible to analyze how clusters are formed according to correlations among indices and how they evolve in time, particularly during times of financial crises. Further analysis is made on the eigenvectors corresponding to the second highest eigenvalues of the correlation matrices, revealing a structure peculiar to markets that operate in different time zones. We also study the survivability of connections and of clusters through time and the influence of noise in centrality measures applied to the networks of financial indices. The results show how the world’s main stock market indices evolved in the last few decades with respect to their clustering structure, how their connections survive in time, and which indices are more central, according to different criteria. In particular, we witness the early formation and evolution of two main clusters, an American and an European one, the formation of a Pacific Asian cluster, and later on, of an Arab cluster. This analysis complements previous studies of the interdependencies of stock markets worldwide

Keywords: networks; financial markets; cluster; evolution (search for similar items in EconPapers)
JEL-codes: E00 G00 (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations: View citations in EconPapers (12)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:iosalg:0023

Access Statistics for this article

Algorithmic Finance is currently edited by Phil Maymin

More articles in Algorithmic Finance from IOS Press
Bibliographic data for series maintained by Saskia van Wijngaarden ().