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Electoral influences on the Brazilian B3 data correlation network

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  • Gerson N. Cardoso
  • Geraldo E. Silva

Abstract

In any society, the relationship between economy and politics is characterized by controversy, enigmas and mysteries. Economic performance affects political results, and the political environment and its process produce financial results. Brazil was hit by economic and political crises from 2012 to 2016. Such crises made it possible to redesign the correlation network between the assets negotiated on the B3 (Brazil Stock Exchange and Over‐the‐Counter Market). This paper aimed to analyse the main aspects related to the topological structure of the assets negotiated on the B3 and its volatility between the pre‐and post‐2014 electoral periods. Results showed the hierarchical clusters and the evolution of the systemic risk, with the banks leading the concentration in the post‐electoral period. The closeness centrality indices for the minimum variance portfolios were modified by approximately 80% between the pre‐electoral and post‐electoral periods. It was concluded that the political events significantly changed the structure, the risk and the possibility of selecting assets for portfolios in the Brazilian market.

Suggested Citation

  • Gerson N. Cardoso & Geraldo E. Silva, 2024. "Electoral influences on the Brazilian B3 data correlation network," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 251-272, January.
  • Handle: RePEc:wly:ijfiec:v:29:y:2024:i:1:p:251-272
    DOI: 10.1002/ijfe.2685
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    as
    1. Erik Snowberg & Justin Wolfers & Eric Zitzewitz, 2007. "Partisan Impacts on the Economy: Evidence from Prediction Markets and Close Elections," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(2), pages 807-829.
    2. Knight*, Brian, 2007. "Are policy platforms capitalized into equity prices? Evidence from the Bush/Gore 2000 Presidential Election," Journal of Public Economics, Elsevier, vol. 91(1-2), pages 389-409, February.
    3. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    4. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    5. Covi, Giovanni & Gorpe, Mehmet Ziya & Kok, Christoffer, 2021. "CoMap: Mapping Contagion in the Euro Area Banking Sector," Journal of Financial Stability, Elsevier, vol. 53(C).
    6. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    7. Huang, Wei-Qiang & Yao, Shuang & Zhuang, Xin-Tian & Yuan, Ying, 2017. "Dynamic asset trees in the US stock market: Structure variation and market phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 94(C), pages 44-53.
    8. Chen, Junping & Xiong, Xiong & Zhu, Jie & Zhu, Xiaoneng, 2017. "Asset prices and economic fluctuations: The implications of stochastic volatility," Economic Modelling, Elsevier, vol. 64(C), pages 128-140.
    9. Gabriele Galati & Richhild Moessner, 2013. "Macroprudential Policy – A Literature Review," Journal of Economic Surveys, Wiley Blackwell, vol. 27(5), pages 846-878, December.
    10. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    11. Ms. Yevgeniya Korniyenko & Manasa Patnam & Rita Maria del Rio-Chanon & Mason A. Porter, 2018. "Evolution of the Global Financial Network and Contagion: A New Approach," IMF Working Papers 2018/113, International Monetary Fund.
    12. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciché & N. Vandewalle & R. Mantegna, 2004. "Networks of equities in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 363-371, March.
    13. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    14. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    15. David Leblang & Bumba Mukherjee, 2005. "Government Partisanship, Elections, and the Stock Market: Examining American and British Stock Returns, 1930–2000," American Journal of Political Science, John Wiley & Sons, vol. 49(4), pages 780-802, October.
    16. Eom, Cheoljun & Park, Jong Won, 2017. "Effects of common factors on stock correlation networks and portfolio diversification," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 1-11.
    17. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
    18. Bilal Ahmed Memon & Hongxing Yao & Rabia Tahir, 2020. "General election effect on the network topology of Pakistan’s stock market: network-based study of a political event," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-14, December.
    19. Bednarek, Ziemowit & Patel, Pratish, 2018. "Understanding the outperformance of the minimum variance portfolio," Finance Research Letters, Elsevier, vol. 24(C), pages 175-178.
    20. Liusha Yang & Romain Couillet & Matthew R. McKay, 2015. "A Robust Statistics Approach to Minimum Variance Portfolio Optimization," Papers 1503.08013, arXiv.org.
    21. Beck, Nathaniel, 1982. "Parties, Administrations, and American Macroeconomic Outcomes," American Political Science Review, Cambridge University Press, vol. 76(1), pages 83-93, March.
    22. Changqing, Luo & Chi, Xie & Cong, Yu & Yan, Xu, 2015. "Measuring financial market risk contagion using dynamic MRS-Copula models: The case of Chinese and other international stock markets," Economic Modelling, Elsevier, vol. 51(C), pages 657-671.
    23. Pop, Petrică C., 2020. "The generalized minimum spanning tree problem: An overview of formulations, solution procedures and latest advances," European Journal of Operational Research, Elsevier, vol. 283(1), pages 1-15.
    24. Boginski, Vladimir & Butenko, Sergiy & Pardalos, Panos M., 2005. "Statistical analysis of financial networks," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 431-443, February.
    25. William D. Nordhaus, 1975. "The Political Business Cycle," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 42(2), pages 169-190.
    26. Charu Sharma & Amber Habib, 2019. "Mutual information based stock networks and portfolio selection for intraday traders using high frequency data: An Indian market case study," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-19, August.
    27. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, November.
    28. Scherer, Bernd, 2011. "A note on the returns from minimum variance investing," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 652-660, September.
    29. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.
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