Collective correlations, dynamics, and behavioural inconsistencies of the cryptocurrency market over time

TL;DR

This study introduces new methods to analyze the evolving correlation, collective dynamics, and volatility behaviors of the top 52 cryptocurrencies from 2019 to mid-2021, revealing key market phenomena.

Contribution

It applies a novel turning point algorithm to identify market regimes and uncovers the inverse relationship between market size and collective dynamics, as well as volatility dispersion during crashes.

Findings

Inverse relationship between market size and collective dynamics.

Greater consistency between size and volatility than size and returns.

Increased volatility uniformity during market crashes.

Abstract

This paper introduces new methods to study behaviours among the 52 largest cryptocurrencies between 01-01-2019 and 30-06-2021. First, we explore evolutionary correlation behaviours and apply a recently proposed turning point algorithm to identify regimes in market correlation. Next, we inspect the relationship between collective dynamics and the cryptocurrency market size - revealing an inverse relationship between the size of the market and the strength of collective dynamics. We then explore the time-varying consistency of the relationships between cryptocurrencies' size and their returns and volatility. There, we demonstrate that there is greater consistency between size and volatility than size and returns. Finally, we study the spread of volatility behaviours across the market changing with time by examining the structure of Wasserstein distances between probability density functions of rolling volatility. We demonstrate a new phenomenon of increased uniformity in volatility during market crashes, which we term \emph{volatility dispersion}.