  Using data from world stock exchange indices prior to and during periods of
global financial crises, clusters and networks of indices are built for
different 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.
