IDEAS home Printed from https://ideas.repec.org/p/ise/remwps/wp03022023.html
   My bibliography  Save this paper

The Dynamics of Exchange Traded Funds: a geometrical and topological approach

Author

Listed:
  • Lucas Paiva de Carvalho
  • Tanya Araújo

Abstract

Using a metric related to the returns correlation, a method is applied to the reconstruction of an economic space from Exchange-Traded Funds (ETFs) data. In the past, the same method was used in a geometrical analysis of times series of stock returns implying that the most of the systematic information of that market is contained in a space of small dimension. Here we have worked with ten years of daily returns of 85 ETF securities and the same dimensional reduction was obtained. Having a metric defined in the space of ETF securities, a topological approach is used to define a complete network of ETFs and its corresponding Minimum Spanning Tree (MST). An outstanding separation of the two main classes of securities over the MST is uncovered. The dimensional reduction as well as the uncovered pattern in the topological structure, they both emerge from the data itself rather than from any modelling resolution.

Suggested Citation

  • Lucas Paiva de Carvalho & Tanya Araújo, 2023. "The Dynamics of Exchange Traded Funds: a geometrical and topological approach," Working Papers REM 2023/0302, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    • Handle: RePEc:ise:remwps:wp03022023
    as

    Download full text from publisher

    File URL: https://rem.rc.iseg.ulisboa.pt/wps/pdf/REM_WP_0302_2023.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. P. Giudici & A. Spelta, 2016. "Graphical Network Models for International Financial Flows," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 128-138, January.
    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. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    2. Erick Treviño Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-31, October.
    3. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    4. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    5. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2019. "Smart network based portfolios," Papers 1907.01274, arXiv.org.
    6. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.
    7. Erick Trevi~no Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," Papers 2004.06676, arXiv.org.
    8. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2022. "Smart network based portfolios," Annals of Operations Research, Springer, vol. 316(2), pages 1519-1541, September.
    9. Nicola, Giancarlo & Cerchiello, Paola & Aste, Tomaso, 2020. "Information network modeling for U.S. banking systemic risk," LSE Research Online Documents on Economics 107563, London School of Economics and Political Science, LSE Library.
    10. Champagne, Claudia, 2014. "The international syndicated loan market network: An “unholy trinity”?," Global Finance Journal, Elsevier, vol. 25(2), pages 148-168.
    11. Trindade, Graça & Dias, José G. & Ambrósio, Jorge, 2017. "Extracting clusters from aggregate panel data: A market segmentation study," Applied Mathematics and Computation, Elsevier, vol. 296(C), pages 277-288.
    12. Assaf Almog & Ferry Besamusca & Mel MacMahon & Diego Garlaschelli, 2015. "Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-16, July.
    13. João A. Bastos & Jorge Caiado, 2014. "Clustering financial time series with variance ratio statistics," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2121-2133, December.
    14. Sebastiano Michele Zema & Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2025. "Mesoscopic structure of the stock market and portfolio optimization," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 20(2), pages 307-333, April.
    15. Guido Caldarelli & Matthieu Cristelli & Andrea Gabrielli & Luciano Pietronero & Antonio Scala & Andrea Tacchella, 2012. "A Network Analysis of Countries’ Export Flows: Firm Grounds for the Building Blocks of the Economy," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-11, October.
    16. Michelle B Graczyk & Sílvio M Duarte Queirós, 2017. "Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    17. Shamshuritawati Sharif, 2012. "Correlation Network Analysis of International Postgraduate Students’ Satisfaction in Top Malaysian Universities: A Robust Approach," Modern Applied Science, Canadian Center of Science and Education, vol. 6(12), pages 1-91, December.
    18. Trancoso, Tiago, 2014. "Emerging markets in the global economic network: Real(ly) decoupling?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 499-510.
    19. Ixandra Achitouv, 2025. "Dynamical analysis of financial stocks network: Improving forecasting using network properties," PLOS ONE, Public Library of Science, vol. 20(5), pages 1-23, May.
    20. López Pérez, Mario & Mansilla Corona, Ricardo, 2022. "Ordinal synchronization and typical states in high-frequency digital markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ise:remwps:wp03022023. 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: Sandra Araújo (email available below). General contact details of provider: https://rem.rc.iseg.ulisboa.pt/ .

    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.