Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June 2015 to January 2016 and from January 2016 to September 2016, corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer, respectively. 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 Michel Temer's period is more risky in terms of volatility transmission network structure. Also, we found evidence of network structure and stock performance relationship.
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