Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Kyoto, 606-8306, Japan.
RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program, Saitama, 351-0198, Japan.
Sci Rep. 2023 Mar 22;13(1):4718. doi: 10.1038/s41598-023-31881-5.
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.
加密资产在数字经济时代变得至关重要。XRP 是市值较大的加密资产之一。在这里，我们为 Ripple 网络开发了一种新的相关张量谱方法，它可以为 XRP 价格提供早期指示。通过对一周内的所有交易进行汇总，构建了一个由 XRP 钱包之间的加权有向每周交易网络。然后，通过将每周网络嵌入连续向量空间，为每个节点获得一个向量。从一组每周节点向量快照中，我们构建了一个相关张量。相关张量的双奇异值分解给出了它的奇异值。通过与随机对照比较，显示了奇异值的重要性。奇异值的演化表现出独特的行为。最大奇异值与 XRP/USD 价格呈显著负相关。我们观察到，在 2018 年 1 月的第一周，XRP/USD 价格峰值期间，最大奇异值的最小值。通过将相关张量分解为信号和噪声分量，以及通过社区结构的演化，解释了 2018 年 1 月最大奇异值的最小值。
