Analysis of similarities between stock and cryptocurrency series by using graphs and spanning trees

Abstract

We investigate similarities and differences between stock and cryptocurrency networks obtained from log-return and volatility time series. We constructed correlation and Fast Fourier Transform based graphs and minimum spanning trees from a set of 100 highly capitalized cryptocurrencies and 100 highly capitalized NASDAQ stocks over a time window of fixed length. Our analysis is based on comparison between both economies in terms of network properties. We also examined distributions of node degrees and edge weights. Our results show that cryptocurrencies and companies with high capitalization tend to correspond to central and densely connected nodes. Network topologies for both economies and node degree distributions are rather similar. Nevertheless, the crypto-economy is more correlated and more strongly linked to important nodes, unlike the graphs of NASDAQ stocks, where we observed clusters of nodes having small dissimilarities.