Nonlinear dependencies on Brazilian equity network from mutual information minimum spanning trees
A. Q. Barbi and
G. A. Prataviera
Papers from arXiv.org
Abstract:
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.
Date: 2017-11, Revised 2019-05
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Published in Physica A: Statistical Mechanics and its Applications, Volume 523, 1 June 2019, Pages 876-885
Downloads: (external link)
http://arxiv.org/pdf/1711.06185 Latest version (application/pdf)
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:arx:papers:1711.06185
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().