Dependency structures in cryptocurrency market from high to low frequency

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 across time horizons from high (15 seconds) 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 inter-and intrasector realizations.

The Cryptocurrency Market in Transition before and after COVID-19: An Opportunity for Investors?

“…However, they only account for a small portion of the existing literature. For example, Antonio et al [ 29 ] used small frequency resolutions such as one hour and four hours and also consider daily data of 25 large market capitalized entities traded on the FTX exchange to discover the evolution of cryptocurrency network structures between different time frequencies. By using Pearson correlation-based MST, they found an increase in the complexity of networks’ shape for coarser time resolutions.…”

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“…closed paths of at least three nodes) while retaining the network's representation as simple as possible (i.e. representing only relevant relations among variables characterising the system under analysis) [45]. Prim's algorithm for MST construction sorts all edges' weights (i.e.…”

“…The resulting network has n − 1 edges and retains only the most significant connections, assuring, at the same time, that connectedness' property is fulfilled [71]. For a complete pedagogical exposition of the determination of the MST, the interested reader is referred to the works by [46,45]. Despite being a powerful method to capture meaningful relationships in network structures describing complex systems, MST presents some aspects that can be unsatisfactory.…”

“…A nested hierarchy emerges from these cliques [79]: dimensionality is reduced in a deterministic manner while local information and the global hierarchical structure of the original network are retained. For a complete pedagogical exposition of the determination of the PMFG and a detailed analysis of its properties, the interested reader is referred to the works by [63,47,45]. The PMFG represents a substantial step forward compared to the MST.…”

“…The number of nodes defines the size of the network, and the number of links establishes the network's sparsity (or, conversely, density). Reversible interactions between components are represented through undirected links, while non-reversible interactions are represented as direct links [45]. Topologically constrained networks, also known as information filtering networks (IFNs), constitute a family of graphs built imposing topological constraints (such as being a tree or a planar graph) while optimising global properties (such as the likelihood) [46,47,48,49].…”