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Multiscale network for 20 stock markets using DCCA

Author

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  • Pereira, Eder Johnson de Area Leão
  • Ferreira, Paulo Jorge Silveira
  • Silva, Marcus Fernandes da
  • Miranda, Jose Garcia Vivas
  • Pereira, H.B. B.

Abstract

The aim of this paper is to analyze the stock exchanges for a large set of countries (20 in total) before and after the subprime crisis, identifying which markets are the most central and if the linkage pattern changed after the crisis. We started by calculating the correlations between stock markets’ returns, using the ρDCCA, in order to identify if there is some variation in the scale between the links in the different stock markets of the network, in both periods. Additionally, a cross-correlation filtering process will be performed with the intention of identifying which countries have stronger relationships according to the used time scales. The results show the central role of European markets among the world’s main financial markets, mainly France, Germany and the United Kingdom. Moreover, after the subprime crisis we find the formation of two large communities, one of European and American countries and the other formed by Asian countries plus Australia, while in the pre-crisis period three communities could be identified. It is possible to conclude that after the 2008 crisis the connectivity and integration of the network for the whole set of analyzed timescales increased.

Suggested Citation

  • Pereira, Eder Johnson de Area Leão & Ferreira, Paulo Jorge Silveira & Silva, Marcus Fernandes da & Miranda, Jose Garcia Vivas & Pereira, H.B. B., 2019. "Multiscale network for 20 stock markets using DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 529(C).
    • Handle: RePEc:eee:phsmap:v:529:y:2019:i:c:s0378437119309069
    DOI: 10.1016/j.physa.2019.121542
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    Citations

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    Cited by:

    1. Beibei Zhang & Xuemei Xie & Chunmei Li, 2023. "How Connected Is China’s Systemic Financial Risk Contagion Network?—A Dynamic Network Perspective Analysis," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    2. Liu, Chao & Fan, Yixin & Xie, Qiwei & Wang, Chao, 2022. "Market-based versus bank-based financial structure in China: From the perspective of financial risk," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 24-39.
    3. Huang, Xiaohong & Huang, Shupei, 2020. "Identifying the comovement of price between China's and international crude oil futures: A time-frequency perspective," International Review of Financial Analysis, Elsevier, vol. 72(C).
    4. de Area Leão Pereira, Eder Johnson & de Santana Ribeiro, Luiz Carlos & da Silva Freitas, Lúcio Flávio & de Barros Pereira, Hernane Borges, 2020. "Brazilian policy and agribusiness damage the Amazon rainforest," Land Use Policy, Elsevier, vol. 92(C).
    5. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    6. Su, Zhi & Xu, Fuwei, 2021. "Dynamic identification of systemically important financial markets in the spread of contagion: A ripple network based collective spillover effect approach," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    7. Mbatha, Vusisizwe Moses & Alovokpinhou, Sedjro Aaron, 2022. "The structure of the South African stock market network during COVID-19 hard lockdown," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    8. Melike E. Bildirici & Memet Salman & Özgür Ömer Ersin, 2022. "Nonlinear Contagion and Causality Nexus between Oil, Gold, VIX Investor Sentiment, Exchange Rate and Stock Market Returns: The MS-GARCH Copula Causality Method," Mathematics, MDPI, vol. 10(21), pages 1-16, October.
    9. Pereira, Hernane Borges de Barros & Rosário, Raphael Silva do & Pereira, Eder Johnson de Area Leão & Moreira, Davidson Martins & Ferreira, Paulo & Miranda, José Garcia Vivas, 2022. "Network dynamic and stability on European Union," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    10. Bossman, Ahmed & Umar, Zaghum & Agyei, Samuel Kwaku & Junior, Peterson Owusu, 2022. "A new ICEEMDAN-based transfer entropy quantifying information flow between real estate and policy uncertainty," Research in Economics, Elsevier, vol. 76(3), pages 189-205.
    11. Anokye M. Adam & Kwabena Kyei & Simiso Moyo & Ryan Gill & Emmanuel N. Gyamfi, 2022. "Multifrequency network for SADC exchange rate markets using EEMD-based DCCA," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(1), pages 145-166, January.
    12. Herrera, Gabriel Paes & Constantino, Michel & Su, Jen-Je & Naranpanawa, Athula, 2022. "Renewable energy stocks forecast using Twitter investor sentiment and deep learning," Energy Economics, Elsevier, vol. 114(C).

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