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Projecting XRP price burst by correlation tensor spectra of transaction networks

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  • Abhijit Chakraborty
  • Tetsuo Hatsuda
  • Yuichi Ikeda

Abstract

Cryptoassets are becoming essential in the digital economy era. XRP is one of the large market cap cryptoassets. Here, we develop a novel method of correlation tensor spectra for the dynamical XRP networks, which can provide an early indication for XRP price. A weighed directed weekly transaction network among XRP wallets is constructed by aggregating all transactions for a week. A vector for each node is then obtained by embedding the weekly network in continuous vector space. From a set of weekly snapshots of node vectors, we construct a correlation tensor. A double singular value decomposition of the correlation tensors gives its singular values. The significance of the singular values is shown by comparing with its randomize counterpart. The evolution of singular values shows a distinctive behavior. The largest singular value shows a significant negative correlation with XRP/USD price. We observe the minimum of the largest singular values at the XRP/USD price peak during the first week of January 2018. The minimum of the largest singular value during January 2018 is explained by decomposing the correlation tensor in the signal and noise components and also by evolution of community structure.

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  • 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.
  • Handle: RePEc:arx:papers:2211.03002
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    References listed on IDEAS

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    1. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    2. Jiaqi Liang & Linjing Li & Daniel Zeng, 2018. "Evolutionary dynamics of cryptocurrency transaction networks: An empirical study," Papers 1808.08585, arXiv.org.
    3. Abhijit Chakraborty & Soumya Easwaran & Sitabhra Sinha, 2016. "Deviations from universality in the fluctuation behavior of a heterogeneous complex system reveal intrinsic properties of components: The case of the international currency market," Papers 1606.06111, arXiv.org, revised Jun 2018.
    4. Koutmos, Dimitrios, 2018. "Bitcoin returns and transaction activity," Economics Letters, Elsevier, vol. 167(C), pages 81-85.
    5. Paolo Tasca & Adam Hayes & Shaowen Liu, 2018. "The evolution of the bitcoin economy," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 19(2), pages 94-126, March.
    6. Abhijit Chakraborty & Soumya Easwaran & Sitabhra Sinha, 2020. "Uncovering the hierarchical structure of the international FOREX market by using similarity metric between the fluctuation distributions of currencies," Papers 2005.02482, arXiv.org.
    7. Chakraborty, Abhijit & Easwaran, Soumya & Sinha, Sitabhra, 2018. "Deviations from universality in the fluctuation behavior of a heterogeneous complex system reveal intrinsic properties of components: The case of the international currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 599-610.
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    Cited by:

    1. 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).

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