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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.
Chaos (Woodbury, N.Y.)
|August 3, 2018
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.
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.
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