Mapping Cryptocurrency Influence with Time-Varying Granger Causality Networks

Summary

This study maps changing relationships among cryptocurrencies using high-frequency returns from 2020 to 2025. It creates weighted, directed networks from statistically significant Granger causal links between asset log returns, treating link direction and strength as measures of influence. It also examines normalized return distributions and ranks assets by their network out-strength.

The analysis reports heavy-tailed normalized returns and a concentration of network influence among a small subset of cryptocurrencies. Ethereum is reported as the most influential asset across the period, while Bitcoin's relative influence gradually declines. The rankings also vary substantially over time, with different cryptocurrencies moving into and out of top positions. This suggests the ecosystem's influence structure is competitive and unstable. The description does not provide network construction thresholds, validation details, or evidence that Granger links establish structural causation, so the rankings should be read as measures within this framework rather than definitive causal or trading signals.

Key ideas

• The study builds weighted directed networks from significant Granger causal relationships in cryptocurrency returns.
• Normalized cryptocurrency returns are reported to have heavy tails.
• A small subset of assets accounts for a disproportionate share of network influence.
• Ethereum ranks as the most influential asset, while Bitcoin's relative importance declines over time.
• Influence rankings change substantially, indicating a non-stable network hierarchy.

Tags

# Time-dependent weighted directed networks of cryptocurrency interaction from high-frequency returns


# Time-dependent weighted directed networks of cryptocurrency interaction from high-frequency returns









We investigate the evolving structure of interactions in cryptocurrency markets using a network-based framework constructed from high-frequency price data spanning 2020-2025. Directed and weighted networks are constructed from statistically significant Granger causal relationships between cryptocurrency log-returns, enabling us to quantify the flow of influence across assets. We find that normalized returns exhibit heavy-tailed distributions, consistent with the presence of large intermittent fluctuations and in line with stylized facts of financial markets. The resulting networks display pronounced heterogeneity in link weights and nodal strengths, indicating that a small subset of cryptocurrencies contributes disproportionately to market dynamics. By ranking cryptocurrencies based on their nodal out-strength, we uncover a dynamically evolving hierarchy of influence. Ethereum consistently emerges as the most influential asset, while Bitcoin shows a gradual decline in its relative importance. The ranking structure exhibits substantial temporal variability, with multiple cryptocurrencies entering and exiting the top positions over time. Our findings reveal a highly competitive and non-stable organization of the cryptocurrency ecosystem.

Shown in full with attribution under the source's licence. Licence: abstract CC0

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