Ⅱ
Monetary Flow
”Dynamic relationship between XRP price and correlation tensor spectra of the transaction network”
Abhijit Chakraborty, Tetsuo Hatsuda, Yuichi Ikeda
Journal Physica A: Statistical Mechanics and its Applications arXiv: 2309.05935, 2024/03
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 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.
”Acquiring Semantic Mode Signal from Tweets of Cryptoassets”
Hiroshi Uehara, Wataru Souma, Yuichi Ikeda
JPS Conf. Proc. 40, 011006 (2023)
This study proposes a method for detecting collective motions, the time series situation where dispersed information becomes inclined to a unique direction. Our proposal, Semantic mode signal, is distinctive among related methods in providing the situation with semantic contexts extracted from time series texts. Furthermore, the proposal is characterized by its applicability to high-dimensional word space with sparsity, such as numerous tweets. We applied the method to tweets concerning 19 cryptoassets. The empirical results indicated that the method appropriately detected the collective motions representing the contexts semantically coincident with the news events and the price trends, supporting the efficiency of our proposal.
”Hodge Decomposition of the Remittance Network on the XRP Ledger in the Price Hike of January 2018”
Yuichi Ikeda, Abhijit Chakraborty
JPS Conf. Proc. 40, 011004 (2023)
This study analyzes the remittance transaction recorded on the XRP ledger for ETH and USD from July 2017 to Jun 2018, including the bubble period in early 2018. Using the Hodge decomposition, we estimate the “loop flow” in the international remittance of cryptoassets during the bubble period. We found characteristic differences between those fiat currencies and cryptoassets during the bubble period. For ETH, there was a significant increase in the loop flow during the cryptoasset price peak. This might be related to money laundering or arbitrage transaction. There was a slight increase in the loop flow for USD during the cryptoasset price peak.
”Embedding and Correlation Tensor for XRP Transaction Networks”
Abhijit Chakraborty, Tetsuo Hatsuda, Yuichi Ikeda
JPS Conf. Proc, 40, 011003 (2023)
Cryptoassets are growing rapidly worldwide. One of the large cap cryptoassets is XRP. In this article, we focus on analyzing transaction data for the 2017–2018 period that consist one of the significant XRP market price bursts. We construct weekly weighted directed networks of XRP transactions. These weekly networks are embedded on continuous vector space using a network embedding technique that encodes structural regularities present in the network structure in terms of node vectors. Using a suitable time window we calculate a correlation tensor. A double singular value decomposition of the correlation tensor provides key insights about the system. The significance of the correlation tensor is captured using a randomized correlation tensor. We present a detailed dependence of correlation tensor on model parameters.
”Projecting XRP Price Burst by Correlation Tensor Spectra of Transaction Networks”
Abhijit Chakraborty, Tetsuo Hatsuda, Yuichi Ikeda
Scientific Reports, 13, 4718 (2023)
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.
”Cryptoasset networks: Flows and regular players in Bitcoin and XRP”
Hideaki Aoyama, Yoshi Fujiwara, Yoshimasa Hidaka, Yuichi Ikeda
PLOS ONE , 0273068, 2022/08
Cryptoassets flow among players as recorded in the ledger of blockchain for all the transactions, comprising a network of players as nodes and flows as edges. The last decade, on the other hand, has witnessed repeating bubbles and crashes of the price of cryptoassets in exchange markets with fiat currencies and other cryptos. We study the relationship between these two important aspects of dynamics, one in the bubble/crash of price and the other in the daily network of crypto, by investigating Bitcoin and XRP. We focus on “regular players” who frequently appear on a weekly basis during a period of time including bubble/crash, and quantify each player’s role with respect to outgoing and incoming flows by defining flow-weighted frequency. During the most significant period of one-year starting from the winter of 2017, we discovered the structure of three groups of players in the diagram of flow-weighted frequency, which is common to Bitcoin and XRP in spite of the different nature of the two cryptos. By examining the identity and business activity of some regular players in the case of Bitcoin, we can observe different roles of them, namely the players balancing surplus and deficit of cryptoassets (Bal-branch), those accumulating the cryptoassets (In-branch), and those reducing it (Out-branch). Using this information, we found that the regime switching among Bal-, In-, Out-branches was presumably brought about by the regular players who are not necessarily dominant and stable in the case of Bitcoin, while such players are simply absent in the case of XRP. We further discuss how one can understand the temporal transitions among the three branches.
”Regional economic integration via detection of circular flow in international value-added network”
Sotaro Sada, Yuichi Ikeda
PLOS ONE 16(8): e0255698, 2021/08
Global value chains are formed through value-added trade, and some regions promote economic integration by concluding regional trade agreements to promote these chains. However, it has not been established to quantitatively assess the scope and extent of economic integration involving various sectors in multiple countries. In this study, we used the World Input–Output Database to create a cross-border sector-wise network of trade in value-added (international value-added network) covering the period of 2000–2014 and evaluated them using network science methods. By applying Infomap to the international value-added network, we confirmed two regional communities: Europe and the Pacific Rim. We applied Helmholtz–Hodge decomposition to the value-added flows within the region into potential and circular flows, and clarified the annual evolution of the potential and circular relationships between countries and sectors. The circular flow component of the decomposition was used to define an economic integration index. Findings confirmed that the degree of economic integration in Europe declined sharply after the economic crisis in 2009 to a level lower than that in the Pacific Rim. The European economic integration index recovered in 2011 but again fell below that of the Pacific Rim in 2013. Moreover, sectoral economic integration indices suggest what Europe depends on Russia in natural resources makes the European economic integration index unstable. On the other hand, the indices of the Pacific Rim suggest the steady economic integration index of the Pacific Rim captures the stable global value chains from natural resources to construction and manufactures of motor vehicles and high-tech products.
”Location-sector analysis of international profit shifting on a multilayer ownership-tax network”
T. Nakamoto, O. Rouhban, Y. Ikeda
Evolutionary and Institutional Economics Review, 17, 219-241, 2020/01
Currently all countries including developing countries are expected to utilize their own tax revenues and carry out their own development for solving poverty in their countries. However, developing countries cannot earn tax revenues like developed countries partly because they do not have effective countermeasures against international tax avoidance. Our analysis focuses on treaty shopping among various ways to conduct international tax avoidance because tax revenues of developing countries have been heavily damaged through treaty shopping. To analyze the location and sector of conduit firms likely to be used for treaty shopping, we constructed a multilayer ownership-tax network and proposed multilayer centrality. Because multilayer centrality can consider not only the value flowing in the ownership network but also the withholding tax rate, it is expected to grasp precisely the locations and sectors of conduit firms established for the purpose of treaty shopping. Our analysis shows that firms in the sectors of Finance and Insurance and Wholesale and Retail trade etc. are involved with treaty shopping. We suggest that developing countries make a clause focusing on these sectors in the tax treaties they conclude.
”Reconstruction of Interbank Network using Ridge Entropy Maximization Model”
Y. Ikeda, H. Takeda
Journal of Economic Interaction and Coordination
arXiv:2001.04097, 2020/01
We develop a network reconstruction model based on entropy maximization considering the sparsity of networks. We reconstruct the interbank network in Japan from financial data in individual banks' balance sheets using the developed reconstruction model from 2000 to 2016. The observed sparsity of the interbank network is successfully reproduced. We examine the characteristics of the reconstructed interbank network by calculating important network attributes. We obtain the following characteristics, which are consistent with the previously known stylized facts. Although we do not introduce the mechanism to generate the core and peripheral structure, we impose the constraints to consider the sparsity that is no transactions within the same bank category except for major commercial banks, the core and peripheral structure has spontaneously emerged. We identify major nodes in each community using the value of PageRank and degree to examine the changing role of each bank category. The observed changing role of banks is considered a result of the quantitative and qualitative monetary easing policy started by the Bank of Japan in April 2013.
”Identification of Key Companies for International Profit Shifting in the Global Ownership Network”
T. Nakamoto, A. Chakraborty, Y. Ikeda
Applied Network Science, 4, 58, 1-26, 2019/08
In the global economy, the intermediate companies owned by multinational corporations (MNCs) have become important players in policy issue, influencing the international profit shifting and diversion of foreign direct investment (FDI). The purpose of this analysis is to identify and analyze high-risk intermediate companies used for international profit shifting. To achieve this aim, we propose a model that focuses on the structure of MNC’s ownership of each affiliate. On the basis of the information in the Orbis database, we constructed the Global Ownership Network (GON) to reflect the relationship between MNCs and intermediate companies. Moreover, we analyzed large MNCs listed in Fortune Global 500. In this analysis, we confirmed the validity of this model by identifying affiliates playing an important role in international tax avoidance. We found that intermediate companies are mainly based in the Netherlands and the United Kingdom, etc., and these companies are located in the jurisdictions favorably to treaty shopping. And it was found that such key companies are concentrated in the IN component of the bow-tie structure, which is the giant weakly connected component with the GON. Therefore, this clarifies that the key companies are geographically located in specific jurisdictions and concentrates on the specific GON components. The key companies are located in the areas that facilitate treaty shopping. Depending on the location of the MNCs, a difference is remarked in the jurisdiction where key companies are located.
”Identification of conduit jurisdictions and community structures in the withholding tax network”
T. Nakamoto, Y. Ikeda
Evolutionary and Institutional Economics Review, 15, 2, 477-493, 2018/12
Due to economic globalization, international tax avoidance has emerged as a well-known global issue. To contribute to providing the solution of international tax avoidance, we tried to investigate which part of the network is vulnerable. Specifically, focusing on treaty shopping, which is one of the international tax avoidance schemes, we attempt to find which jurisdictions are likely to be used for treaty shopping from the viewpoint of tax rates and reveal the relationships between jurisdictions used for treaty shopping and the others. For that purpose, based on withholding tax rates imposed on dividends, interest, and royalties, we produced the withholding tax network expressed as weighted graphs, computed the centralities and detected the communities. As a result, we identified the jurisdictions used for treaty shopping and pointed out that there are community structures. The results of our study suggested that fewer jurisdictions need to introduce more regulations for the prevention of treaty shopping worldwide.
"Complex correlation approach for high frequency financial data”
M. Wilinski, Y. Ikeda, H. Aoyama
Journal of Statistical Mechanics: Theory and Experiment, 023405-023405, 2018/01
We propose a novel approach that allows to calculate Hilbert transform based complex correlation for unevenly spaced data. This method is especially suitable for high frequency trading data, which are of a particular interest in finance. Its most important feature is the ability to take into account lead-lag relations on different scales, without knowing them in advance. We also present results obtained with this approach while working on Tokyo Stock Exchange intraday quotations. We show that individual sectors and subsectors tend to form important market components which may follow each other with small but significant delays. These components may be recognized by analysing eigenvectors of complex correlation matrix for Nikkei 225 stocks. Interestingly, sectorial components are also found in eigenvectors corresponding to the bulk eigenvalues, traditionally treated as noise.