Cluster analysis on the structure of the cryptocurrency market via Bitcoin-Ethereum filtering

被引:32
|
作者
Song, Jung Yoon [1 ,2 ]
Chang, Woojin [1 ,3 ]
Song, Jae Wook [4 ]
机构
[1] Seoul Natl Univ, Dept Ind Engn, Seoul 08826, South Korea
[2] Seoul Natl Univ, Inst Ind Syst Innovat, Seoul 08826, South Korea
[3] Seoul Natl Univ, SNU Inst Res Finance & Econ, Seoul 08826, South Korea
[4] Sejong Univ, Dept Data Sci, Seoul 05006, South Korea
基金
新加坡国家研究基金会;
关键词
Cryptocurrency; Market structure; Bitcoin-Ethereum filtering; Clustering; Minimum spanning tree; MINIMUM SPANNING-TREES; TIME-SERIES; HIERARCHICAL STRUCTURE; COLLECTIVE BEHAVIOR; SYSTEMIC RISK; NETWORK; INEFFICIENCY;
D O I
10.1016/j.physa.2019.121339
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The purpose of this research is to analyze the structure of the cryptocurrency market based on the correlation-based agglomerative hierarchical clustering and minimum spanning tree. In order to detect a reasonable and distinct collective behavior among the market entities, we propose a filtering mechanism, called Bitcoin-Ethereum filtering to exclude their linear influences to other cryptocurrencies. In this regard, we carefully examine the market structures for the cases of before and after filtering in terms of the Total, Pre-, and Post-regulation periods. Based on the results, we discover the leadership of the Bitcoin and Ethereum in the market, six homogeneous clusters composed of relatively less-traded cryptocurrencies, and transformation of the market structure after the announcement of regulations from various countries. (C) 2019 Elsevier B.V. All rights reserved
引用
收藏
页数:16
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