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Fractal Analysis of Bitcoin Persistence and Cryptocurrency Market Structure

Article arXiv papers · Author: Esther Cabezas-Rivas et al.
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Summary

This study applies fractal geometry and statistical analysis to Bitcoin returns to examine persistence, predictability, and market structure. It compares nine cryptocurrencies, together representing almost three quarters of market capitalization, with traditional assets including spot and futures commodities, government bonds, stock indices, and growth and value stocks. The paper also considers whether differences in underlying technology are reflected in price dynamics.

The authors report a high degree of persistence in Bitcoin prices, which they associate with lower efficiency and greater predictability. They also find that self-similarity across time scales appears only in fully decentralized cryptocurrencies, suggesting technology may shape observed dynamics. These are conclusions from the assets and analysis described; the supplied text does not specify the sample period, statistical tests, or forecasting evaluation. Persistence and fractal patterns alone do not establish a tradable edge, and the summary provides no evidence about transaction costs or whether the findings hold in later market regimes.

Key ideas

  • The paper uses fractal geometry to study statistical properties of Bitcoin returns.
  • It compares nine cryptocurrencies with a range of traditional assets.
  • The authors report persistent Bitcoin prices and interpret persistence as reducing efficiency while increasing predictability.
  • They report self-similarity across time scales only for fully decentralized cryptocurrencies.
  • The reported findings do not by themselves demonstrate profitable forecasting or trading.

Tags

CryptoStatisticsMulti-assetCommoditiesFixed income
Full text
# Chance or Chaos? Fractal geometry aimed to inspect the nature of Bitcoin


# Chance or Chaos? Fractal geometry aimed to inspect the nature of Bitcoin









The aim of this paper is to analyse the Bitcoin in order to shed some light on its nature and behaviour. We select 9 cryptocurrencies that account for almost 75\% of total market capitalisation and compare their evolution with that of a wide variety of traditional assets: commodities with spot and futures contracts, treasury bonds, stock indices, growth and value stocks. Fractal geometry will be applied to carry out a careful statistical analysis of the performance of the Bitcoin returns. As a main conclusion, we have detected a high degree of persistence in its prices, which decreases the efficiency but increases its predictability. Moreover, we observe that the underlying technology influences price dynamics, with fully decentralised cryptocurrencies being the only ones to exhibit self-similarity features at any time scale.

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

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.