IDEAS home Printed from https://ideas.repec.org/a/ega/rafega/201111.html
   My bibliography  Save this article

Comparando distancias en los mercados financieros mundiales

Author

Listed:
  • Linda Margarita Medina Herrera

    (Tecnológico de Monterrey)

  • Ernesto Pacheco Velázquez

    (Tecnológico de Monterrey)

Abstract

This paper analyzes the correlation of the world main financial indexes. We compare the structure of the minimum spanning tree constructed from the correlation matrix (Euclidean distance) with minimum spanning trees obtained using three Non-Euclidean distances. It is found that indexes in Western Europe, Asia and North America form large clusters, while the indexes of South America, Eastern Europe and Africa are less strong blocks. It is also found that the distances Chi-City Block and City Block best separate clusters and point exactly to the central vertex of the tree. The above distances are preferable to Pearson correlation coefficients to analyze the correlation structure of the trees

Suggested Citation

  • Linda Margarita Medina Herrera & Ernesto Pacheco Velázquez, 2011. "Comparando distancias en los mercados financieros mundiales," Revista de Administración, Finanzas y Economía (Journal of Management, Finance and Economics), Tecnológico de Monterrey, Campus Ciudad de México, vol. 6(2), pages 88-98.
    • Handle: RePEc:ega:rafega:201111
    as

    Download full text from publisher

    File URL: http://alejandria.ccm.itesm.mx/egap/documentos/2011V5A11Medina-Pacheco.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Çukur, Sadik & Eryiğit, Mehmet & Eryiğit, Resul, 2007. "Cross correlations in an emerging market financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 555-564.
    2. Giovanni Bonanno & Nicolas Vandewalle & Rosario N. Mantegna, 2000. "Taxonomy of Stock Market Indices," Papers cond-mat/0001268, arXiv.org, revised Aug 2000.
    3. Eom, Cheoljun & Oh, Gabjin & Jung, Woo-Sung & Jeong, Hawoong & Kim, Seunghwan, 2009. "Topological properties of stock networks based on minimal spanning tree and random matrix theory in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 900-906.
    4. Barthélemy, Marc & Barrat, Alain & Pastor-Satorras, Romualdo & Vespignani, Alessandro, 2005. "Characterization and modeling of weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(1), pages 34-43.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2010. "Topological properties of stock market networks: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3240-3249.
    2. Zhang, Yiting & Lee, Gladys Hui Ting & Wong, Jian Cheng & Kok, Jun Liang & Prusty, Manamohan & Cheong, Siew Ann, 2011. "Will the US economy recover in 2010? A minimal spanning tree study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2020-2050.
    3. Linda Margarita Medina Herrera & Ernesto Armando Pacheco Velázquez, 2012. "Distances And Networks: The Case Of Mexico," Accounting & Taxation, The Institute for Business and Finance Research, vol. 4(2), pages 39-48.
    4. Linda Margarita Medina Herrera & José Benito Díaz Hernández, 2011. "Caracterización y modelado de redes: el caso de la Bolsa Mexicana de Valores," Revista de Administración, Finanzas y Economía (Journal of Management, Finance and Economics), Tecnológico de Monterrey, Campus Ciudad de México, vol. 5(1), pages 23-32.
    5. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    6. Radhakrishnan, Srinivasan & Duvvuru, Arjun & Sultornsanee, Sivarit & Kamarthi, Sagar, 2016. "Phase synchronization based minimum spanning trees for analysis of financial time series with nonlinear correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 259-270.
    7. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2011. "The Japanese economy in crises: A time series segmentation study," Economics Discussion Papers 2011-24, Kiel Institute for the World Economy (IfW Kiel).
    8. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2009. "The expectation hypothesis of interest rates and network theory: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1137-1149.
    9. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    10. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2012. "The Japanese economy in crises: A time series segmentation study," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-81.
    11. Linda Margarita Medina Herrera & Ernesto Armando Pacheco Velazquez, 2013. "Spectral Analysis And Networks In Financial Correlation Matrices, Analisis Espectral Y Redes En Matrices De Correlacion Financiera," Revista Internacional Administracion & Finanzas, The Institute for Business and Finance Research, vol. 6(6), pages 15-28.
    12. Sandoval, Leonidas & Franca, Italo De Paula, 2012. "Correlation of financial markets in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 187-208.
    13. Wang, Gang-Jin & Xie, Chi & Chen, Shou & Yang, Jiao-Jiao & Yang, Ming-Yan, 2013. "Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3715-3730.
    14. Eom, Cheoljun & Kwon, Okyu & Jung, Woo-Sung & Kim, Seunghwan, 2010. "The effect of a market factor on information flow between stocks using the minimal spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1643-1652.
    15. Kazemilari, Mansooreh & Djauhari, Maman Abdurachman, 2015. "Correlation network analysis for multi-dimensional data in stocks market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 62-75.
    16. Vinayak, & Raghuvanshi, Adarsh & kshitij, Avinash, 2023. "Signatures of capacity development through research collaborations in artificial intelligence and machine learning," Journal of Informetrics, Elsevier, vol. 17(1).
    17. D'Arcangelis, Anna Maria & Rotundo, Giulia, 2021. "Herding in mutual funds: A complex network approach," Journal of Business Research, Elsevier, vol. 129(C), pages 679-686.
    18. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    19. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    20. Sandoval, Leonidas, 2014. "To lag or not to lag? How to compare indices of stock markets that operate on different times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 227-243.

    More about this item

    Keywords

    índices Financieros. Correlación. Distancias. Árboles de expansión mínima;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ega:rafega:201111. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: José Antonio Núñez (email available below). General contact details of provider: https://edirc.repec.org/data/emitemx.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.