Dependency structures in cryptocurrency market from high to low frequency

TL;DR

This paper analyzes how the correlation structure of 25 liquid cryptocurrencies changes across different time resolutions, revealing a decrease in correlations at finer scales and a more hierarchical structure at coarser scales.

Contribution

It provides a detailed analysis of the evolution of dependency structures in cryptocurrency markets across multiple time horizons using network methods.

Findings

Correlation decreases at finer time resolutions.

Hierarchical structure becomes more prominent at coarser resolutions.

Mainstream cryptocurrencies play a key reference role in the hierarchy.

Abstract

We investigate logarithmic price returns cross-correlations at different time horizons for a set of 25 liquid cryptocurrencies traded on the FTX digital currency exchange. We study how the structure of the Minimum Spanning Tree (MST) and the Triangulated Maximally Filtered Graph (TMFG) evolve from high (15 s) to low (1 day) frequency time resolutions. For each horizon, we test the stability, statistical significance and economic meaningfulness of the networks. Results give a deep insight into the evolutionary process of the time dependent hierarchical organization of the system under analysis. A decrease in correlation between pairs of cryptocurrencies is observed for finer time sampling resolutions. A growing structure emerges for coarser ones, highlighting multiple changes in the hierarchical reference role played by mainstream cryptocurrencies. This effect is studied both in its pairwise realizations and intra-sector ones.