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Dynamical networks from correlations

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  • Aste, T.
  • Di Matteo, T.

Abstract

The extraction of relevant and meaningful information from large streams of data has become one of the major challenges for scientists working in the field of complex systems. In particular, one of the main goals is to get information about the underlying system of interactions that leads to complex collective dynamics. In this paper, we discuss how a set of relevant interactions can be extracted from the analysis of the cross-correlation matrix. We show that an active and adaptive correlation filtering procedure can be associated to the dynamics of a network which is a sort of ‘hyper-molecule’ warped on a D-dimensional unitary sphere.

Suggested Citation

  • Aste, T. & Di Matteo, T., 2006. "Dynamical networks from correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 156-161.
    • Handle: RePEc:eee:phsmap:v:370:y:2006:i:1:p:156-161
    DOI: 10.1016/j.physa.2006.04.019
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    References listed on IDEAS

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    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. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    3. Di Matteo, T. & Aste, T. & Mantegna, R.N., 2004. "An interest rates cluster analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 181-188.
    4. Di Matteo, T. & Aste, T. & Hyde, S.T. & Ramsden, S., 2005. "Interest rates hierarchical structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 21-33.
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    Citations

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    Cited by:

    1. Pier Francesco Procacci & Tomaso Aste, 2022. "Portfolio optimization with sparse multivariate modeling," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 445-465, October.
    2. 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.
    3. Pier Francesco Procacci & Tomaso Aste, 2021. "Portfolio Optimization with Sparse Multivariate Modelling," Papers 2103.15232, arXiv.org.
    4. Shu-Heng Chen & Sai-Ping Li, 2011. "Econophysics: Bridges over a Turbulent Current," Papers 1107.5373, arXiv.org.
    5. Noemi Nava & T. Di Matteo & Tomaso Aste, 2017. "Dynamic correlations at different time-scales with Empirical Mode Decomposition," Papers 1708.06586, arXiv.org.
    6. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2018. "Dynamic correlations at different time-scales with empirical mode decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 534-544.
    7. Nicolò Musmeci & Vincenzo Nicosia & Tomaso Aste & Tiziana Di Matteo & Vito Latora, 2017. "The Multiplex Dependency Structure of Financial Markets," Complexity, Hindawi, vol. 2017, pages 1-13, September.
    8. Vamvakaris, Michail D. & Pantelous, Athanasios A. & Zuev, Konstantin M., 2018. "Time series analysis of S&P 500 index: A horizontal visibility graph approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 41-51.
    9. Nicol'o Musmeci & Tomaso Aste & Tiziana Di Matteo, 2016. "What does past correlation structure tell us about the future? An answer from network filtering," Papers 1605.08908, arXiv.org.
    10. Biplab Bhattacharjee & Muhammad Shafi & Animesh Acharjee, 2017. "Investigating the Evolution of Linkage Dynamics among Equity Markets Using Network Models and Measures: The Case of Asian Equity Market Integration," Data, MDPI, vol. 2(4), pages 1-28, December.
    11. Musmeci, Nicoló & Nicosia, Vincenzo & Aste, Tomaso & Di Matteo, Tiziana & Latora, Vito, 2017. "The multiplex dependency structure of financial markets," LSE Research Online Documents on Economics 85337, London School of Economics and Political Science, LSE Library.
    12. Antonio Briola & Tomaso Aste, 2022. "Dependency structures in cryptocurrency market from high to low frequency," Papers 2206.03386, arXiv.org, revised Dec 2022.

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