A Multi-Dimensional Study of Cryptocurrency Classification and Capital Rotational Behaviour

Cryptocurrency market movements are complex to understand because they are shaped by market capitalization, systemic influence, and investor capital flows. This study analyses the hierarchy of major cryptocurrencies and the relationship dynamics between them. Eleven crypto-assets observed from 1 January 2021 to 31 December 2025 are classified into four tiers based on market relevance and systemic importance. Weekly smoothed price data are transformed into simple, logarithmic and cumulative returns, and are examined through Pearson correlation, Spearman rank correlation, rolling correlation, ANOVA, DCC-GARCH dynamic correlation modelling, and Hidden Markov Model (HMM)-based regime classification. The findings indicate strong systemic influence from Bitcoin and Ethereum, high interdependence across cryptocurrencies, and evidence of capital rotation from dominant assets to alternative cryptocurrencies during expansionary phases. DCC-GARCH results show that correlation is time-varying, while HMM-DCC results show that correlations are regimedependent, strengthening around Bitcoin during contraction and shifting toward altcoinbenchmark relationships during alt- rotation phases.