A Second-Order Hierarchical Clustering of Cryptocurrencies

Document Type : Research Paper

Author

Department of Accounting and Finance, Faculty of Humanities and Social Sciences, Yazd University, Yazd, Iran

Abstract

The clustering of cryptocurrencies as an emerging field in investment management is the main topic of this research. Applying the information-based distance matrices, we clustered the 30 most valuable cryptocurrencies. Then, we identified the most influential clustering by the concept of Minimum Spanning Tree (MST) and the centrality measures of graph theory. A second-order clustering, which is defined as the clustering of hierarchical clusterings, was applied to cluster 56 dendrograms. Using the most influential clustering, we identified the main clusters of cryptocurrencies and sub-clusters. The results showed that the clustering composition of cryptocurrencies changed at the period I (before COVID-19) and II (pandemic time).

Keywords

Main Subjects

References

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Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies)
Volume 15, Issue 3
July 2022
Pages 569-593

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