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

Abstract

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.