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An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers.

Aurelio F Bariviera1, Luciano Zunino2, Osvaldo A Rosso3

  • 1Department of Business, Universitat Rovira i Virgili, Av. Universitat 1, 43204 Reus, Spain.

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Summary

This study analyzed 12 cryptocurrencies, finding distinct price dynamics. Some digital currencies exhibit persistent stochastic behavior, while others act like a random walk, differentiating blockchain assets.

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Area of Science:

  • Financial Markets
  • Cryptocurrency Dynamics
  • Complexity Science

Background:

  • The cryptocurrency market has experienced significant volatility, with boom and bust cycles.
  • Understanding intraday price dynamics is crucial for market participants.
  • Blockchain technology underpins a diverse range of digital assets.

Purpose of the Study:

  • To analyze the intraday price dynamics of 12 major cryptocurrencies during recent market fluctuations.
  • To differentiate the behavioral patterns of various cryptocurrencies based on their price movements.
  • To assess the impact of market participant behavior on cryptocurrency differentiation.

Main Methods:

  • Utilized the complexity-entropy causality plane to analyze price dynamics.
  • Examined intraday price data for 12 cryptocurrencies, representing over 90% of daily turnover.
  • Employed quantitative methods to identify distinct patterns in cryptocurrency behavior.

Main Results:

  • Identified three distinct dynamic patterns within the analyzed cryptocurrency data.
  • Ethereum Classic (ETC) and Ethereum (ETH) showed more persistent stochastic dynamics.
  • Dash (DASH) and NEM (XEM) exhibited behaviors closer to a random walk.

Conclusions:

  • Cryptocurrencies, despite sharing blockchain technology, display differentiated market behaviors.
  • Market participants distinguish between similar financial assets based on their unique dynamics.
  • The complexity-entropy causality plane is effective in categorizing cryptocurrency price dynamics.