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

TL;DR

This study analyzes the intraday price dynamics of twelve cryptocurrencies using permutation-information-theory quantifiers, revealing distinct stochastic behaviors and patterns that differentiate similar assets in the crypto market.

Contribution

It applies permutation-information-theory quantifiers to characterize and discriminate the complex price dynamics of multiple cryptocurrencies during a recent market boom and bust.

Findings

Most cryptocurrencies follow similar dynamics

ETC and ETH show persistent stochastic behavior

DASH and XEM behave closer to a random walk

Abstract

This paper discusses the dynamics of intraday prices of twelve cryptocurrencies during last months' boom and bust. The importance of this study lies on the extended coverage of the cryptoworld, accounting for more than 90\% of the total daily turnover. By using the complexity-entropy causality plane, we could discriminate three different dynamics in the data set. Whereas most of the cryptocurrencies follow a similar pattern, there are two currencies (ETC and ETH) that exhibit a more persistent stochastic dynamics, and two other currencies (DASH and XEM) whose behavior is closer to a random walk. Consequently, similar financial assets, using blockchain technology, are differentiated by market participants.