  Mutual information minimum spanning trees are used to explore nonlinear
dependencies on Brazilian equity network in the periods from June/01/2015 to
January/26/2016, in which Brazil was under the government of President Dilma
Rousseff, and from January/27/2016 to September/08/2016 which includes the
government transition from President Dilma Rousseff to President Michel Temer.
Minimum spanning trees from mutual information and linear correlation between
stocks returns were obtained and compared. Mutual information minimum spanning
trees present higher degree of robustness and evidence of power law tail in the
weighted degree distribution, indicating more risk in terms of volatility
transmission than it is expected by the analysis based on linear correlation.
In particular, a remarkable increase of stock returns nonlinear dependencies
indicates that the period including the government transition is more risky in
terms of volatility transmission network structure. Also, we found evidence of
network structure and stock performance relationship. Besides, those results
emphasize the usefulness of mutual information network analysis for
identification of Financial Markets features due to nonlinear dependencies.
