Abstract

Cryptocurrencies have become a prominent investment tool recently with increasing interest in them and their relationships with stock and foreign exchange markets. We analyze here the cross-correlations of price changes of different cryptocurrencies using Random Matrix Theory and extract community structures by constructing minimum spanning trees, finding their eigenvalues contrast sharply with universal predictions of Random Matrix Theory. We reveal distinct transient community structures among different groupings of cryptocurrencies. By studying the cross-correlation dynamics of sub-communities we find evidence of collective behaviour. Furthermore, we compare eigenvalue changes and find prominent groupings following a community trend, useful for creating cryptocurrency portfolios.