quant research // summarizing the paperLOADING
Shubhangam Shukla, Mahesh Peyyala, Abhijit Chakraborty · 2026-06-24
The authors build directed, weighted networks of how cryptocurrencies influence each other, using statistically significant Granger-causal links between high-frequency log-returns from 2020-2025. They find influence is concentrated in a few coins, with Ethereum consistently the most influential and Bitcoin gradually declining, while the overall ranking of influential coins shifts substantially over time.
Why it matters: For crypto traders, the framework offers a way to think about which assets tend to lead price movements and how that leadership structure changes, which could inform monitoring of spillover and dependence. Because the influence hierarchy is unstable, it suggests caution about assuming any single coin (even Bitcoin) permanently drives the market.
⚠ This is a descriptive network/statistical study of past data (Granger causality is not true causation) with no trading strategy or out-of-sample profitability tested.
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.
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AI summary generated from the paper’s public abstract via arXiv; it may miss nuance — read the source before relying on it. Thank you to arXiv for its open-access interoperability; StockTools is not affiliated with arXiv, and all rights remain with the authors. Educational only, not financial advice.