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


Article Title [فارسی]

ارائه یک خوشه بندی سلسله مراتبی مرتبه دوم از رمزارزهای منتخب

Author [فارسی]

  • حجت الله صادقی
بخش حسابداری و مالی، پردیس علوم انسانی و اجتماعی، دانشگاه یزد، ایران
Abstract [فارسی]

خوشه بندی ارزهای دیجیتال به عنوان یک زمینه نوظهور در مدیریت سرمایه گذاری موضوع اصلی این تحقیق است. با استفاده از ماتریس های فاصله مبتنی بر اطلاعات، 30 ارز دیجیتال ارزشمند را دسته بندی کردیم. سپس، تأثیرگذارترین خوشه‌بندی را با مفهوم درخت پوشای کمینه (MST) و معیارهای مرکزیت نظریه گراف شناسایی کردیم. یک خوشه بندی مرتبه دوم، که به عنوان خوشه بندی خوشه های سلسله مراتبی تعریف می شود، برای خوشه بندی 56 دندروگرام اعمال شد و در نهایت با استفاده از تأثیرگذارترین خوشه‌بندی، خوشه‌های اصلی ارزهای دیجیتال و زیرخوشه‌ها را شناسایی کردیم. نتایج نشان می‌دهد که ترکیب خوشه‌بندی ارزهای دیجیتال، در دوره اول (قبل از COVID-19) و دوره دوم (زمان همه‌گیری) تغییر کرده است.

Keywords [فارسی]

  • خوشه بندی سلسله مراتبی
  • درخت پوشای کمینه
  • آنتروپی
  • رمزارزها
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