This study investigates whether the macroscopic statistical maturity of cryptocurrencies implies dynamical equivalence with an equity-market benchmark. We analyze one-minute data (2020–2025) for Bitcoin, Ethereum, XRP, and E-mini S&P 500 futures using the Complexity-Entropy Causality Plane (CECP) and directed horizontal visibility graphs (DHVG). While conventional stylized facts overlap across the analyzed assets, cryptocurrencies exhibit weaker local ordinal organization and a larger divergence between their high-degree in- and out-visibility distributions relative to matched surrogate baselines under the primary specification. This high-degree separation is strongest at the one-minute scale and weakens under 5- and 10-minute aggregation, while the direction of the underlying asymmetry remains more asset- and preprocessing-dependent. We therefore conclude only that macroscopic similarity can coexist with diagnostic-specific structural differences in the assets and period examined.
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Kim et al. (2026) studied this question.
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