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Dynamic relationship between the XRP price and correlation tensor spectra of transaction networks

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  • Chakraborty, Abhijit
  • Hatsuda, Tetsuo
  • Ikeda, Yuichi

Abstract

The emergence of cryptoassets has sparked a paradigm shift in the world of finance and investment, ushering in a new era of digital assets with profound implications for the future of currency and asset management. A recent study showed that during the bubble period around the year, 2018, the price of cryptoasset, XRP has a strong anti correlation with the largest singular values of the correlation tensors obtained from the weekly XRP transaction networks. In this study, we provide a detailed analysis of the method of correlation tensor spectra for XRP transaction networks. We calculate and compare the distribution of the largest singular values of the correlation tensor using the random matrix theory with the largest singular values of the empirical correlation tensor. We investigate the correlation between the XRP price and the largest singular values for a period spanning two years. We also uncover the distinct dependence between the XRP price and the singular values for bubble and non-bubble periods. The significance of the time evolution of singular values is shown by comparison with the evolution of singular values of the reshuffled correlation tensor. Furthermore, we identify a set of driver nodes in the transaction networks that drives the market during the bubble period using singular vectors.

Suggested Citation

  • Chakraborty, Abhijit & Hatsuda, Tetsuo & Ikeda, Yuichi, 2024. "Dynamic relationship between the XRP price and correlation tensor spectra of transaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    • Handle: RePEc:eee:phsmap:v:639:y:2024:i:c:s037843712400195x
    DOI: 10.1016/j.physa.2024.129686
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    References listed on IDEAS

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    1. Plerou, V & Gopikrishnan, P & Rosenow, B & Amaral, L.A.N & Stanley, H.E, 2000. "A random matrix theory approach to financial cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 374-382.
    2. B. Podobnik & D. F. Fu & H. E. Stanley & P. Ch. Ivanov, 2007. "Power-law autocorrelated stochastic processes with long-range cross-correlations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 56(1), pages 47-52, March.
    3. 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.
    4. Nicol`o Vallarano & Claudio Tessone & Tiziano Squartini, 2020. "Bitcoin Transaction Networks: an overview of recent results," Papers 2005.00114, arXiv.org, revised Jul 2020.
    5. Graczyk, Michelle B. & Duarte Queirós, Sílvio M., 2018. "Volatility–Trading volume intraday correlation profiles and its nonstationary features," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 28-34.
    6. 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.
    7. Abhijit Chakraborty & Tetsuo Hatsuda & Yuichi Ikeda, 2022. "Projecting XRP price burst by correlation tensor spectra of transaction networks," Papers 2211.03002, arXiv.org, revised May 2023.
    8. D'aniel Kondor & M'arton P'osfai & Istv'an Csabai & G'abor Vattay, 2013. "Do the rich get richer? An empirical analysis of the BitCoin transaction network," Papers 1308.3892, arXiv.org, revised Mar 2014.
    9. Dániel Kondor & Márton Pósfai & István Csabai & Gábor Vattay, 2014. "Do the Rich Get Richer? An Empirical Analysis of the Bitcoin Transaction Network," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-10, February.
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