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Complex networks on hyperbolic surfaces

Author

Listed:
  • Aste, T.
  • Di Matteo, T.
  • Hyde, S.T.

Abstract

We explore a novel method to generate and characterize complex networks by means of their embedding on hyperbolic surfaces. Evolution through local elementary moves allows the exploration of the ensemble of networks which share common embeddings and consequently share similar hierarchical properties. This method provides a new perspective to classify network-complexity both on local and global scale. We demonstrate by means of several examples that there is a strong relation between the network properties and the embedding surface.

Suggested Citation

  • Aste, T. & Di Matteo, T. & Hyde, S.T., 2005. "Complex networks on hyperbolic surfaces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(1), pages 20-26.
    • Handle: RePEc:eee:phsmap:v:346:y:2005:i:1:p:20-26
    DOI: 10.1016/j.physa.2004.08.045
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    Citations

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    Cited by:

    1. Christian Bongiorno & Damien Challet, 2020. "Nonparametric sign prediction of high-dimensional correlation matrix coefficients," Papers 2001.11214, arXiv.org.
    2. Qu, Junyi & Liu, Ying & Tang, Ming & Guan, Shuguang, 2022. "Identification of the most influential stocks in financial networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    3. Anshul Verma & Orazio Angelini & Tiziana Di Matteo, 2019. "A new set of cluster driven composite development indicators," Papers 1911.11226, arXiv.org, revised Mar 2020.
    4. Musmeci, Nicoló & Aste, Tomaso & Di Matteo, T., 2015. "Relation between financial market structure and the real economy: comparison between clustering methods," LSE Research Online Documents on Economics 61644, London School of Economics and Political Science, LSE Library.
    5. 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.
    6. Nicol'o Musmeci & Tomaso Aste & Tiziana Di Matteo, 2014. "Risk diversification: a study of persistence with a filtered correlation-network approach," Papers 1410.5621, arXiv.org.
    7. Xue Guo & Hu Zhang & Tianhai Tian, 2018. "Development of stock correlation networks using mutual information and financial big data," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-16, April.
    8. Nicoló Musmeci & Tomaso Aste & T Di Matteo, 2015. "Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-24, March.
    9. 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.
    10. Antonio Briola & Tomaso Aste, 2022. "Dependency structures in cryptocurrency market from high to low frequency," Papers 2206.03386, arXiv.org, revised Dec 2022.
    11. Akgüller, Ömer & Balcı, Mehmet Ali, 2018. "Geodetic convex boundary curvatures of the communities in stock market networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 569-581.
    12. Nicolo Musmeci & Tomaso Aste & Tiziana Di Matteo, 2014. "Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods," Papers 1406.0496, arXiv.org, revised Jan 2015.
    13. Ren, Yinghua & Zhao, Wanru & You, Wanhai & Zhai, Kaikai, 2021. "Multiscale and partial correlation networks analysis of risk connectedness in global equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    14. Peter Sinka & Peter J. Zeitsch, 2022. "Hedge Effectiveness of the Credit Default Swap Indices: a Spectral Decomposition and Network Topology Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1375-1412, December.
    15. Gang-Jin Wang & Chi Xie & Shou Chen, 2017. "Multiscale correlation networks analysis of the US stock market: a wavelet analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 561-594, October.
    16. M. Raddant & T. Di Matteo, 2023. "A look at financial dependencies by means of econophysics and financial economics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(4), pages 701-734, October.
    17. Vishwas Kukreti & Hirdesh K. Pharasi & Priya Gupta & Sunil Kumar, 2020. "A perspective on correlation-based financial networks and entropy measures," Papers 2004.09448, arXiv.org.
    18. Giuseppe Brandi & T. Di Matteo, 2020. "A new multilayer network construction via Tensor learning," Papers 2004.05367, arXiv.org.
    19. Tomaso Aste & Ruggero Gramatica & T. Di Matteo, 2011. "Exploring complex networks via topological embedding on surfaces," Papers 1107.3456, arXiv.org, revised Aug 2012.
    20. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2019. "Latent factor models for credit scoring in P2P systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 112-121.
    21. 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.
    22. Sudarshan Kumar & Tiziana Di Matteo & Anindya S. Chakrabarti, 2020. "Disentangling shock diffusion on complex networks: Identification through graph planarity," Papers 2001.01518, arXiv.org.
    23. Arnav Hiray & Pratvi Shah & Vishwa Shah & Agam Shah & Sudheer Chava & Mukesh Tiwari, 2023. "Shifting Cryptocurrency Influence: A High-Resolution Network Analysis of Market Leaders," Papers 2307.16874, arXiv.org, revised Jan 2024.
    24. Tomaso Aste & T. Di Matteo, 2017. "Sparse Causality Network Retrieval from Short Time Series," Complexity, Hindawi, vol. 2017, pages 1-13, November.
    25. Vidal-Tomás, David & Briola, Antonio & Aste, Tomaso, 2023. "FTX's downfall and Binance's consolidation: the fragility of centralised digital finance," LSE Research Online Documents on Economics 119902, London School of Economics and Political Science, LSE Library.

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