Classification of cryptocurrency coins and tokens by the dynamics of their market capitalisations

TL;DR

This paper analyzes the market capitalization distributions of cryptocurrencies, revealing distinct power-law behaviors for coins and tokens, and models their growth dynamics to explain their different market roles and future convergence trends.

Contribution

It introduces a simple proportional growth model to explain the differing market cap distributions of coins and tokens, validated with empirical data.

Findings

Coins follow a power-law with exponent 0.5-0.7.

Tokens follow a power-law with exponent 1.0-1.3.

Model predictions align well with empirical data.

Abstract

We empirically verify that the market capitalisations of coins and tokens in the cryptocurrency universe follow power-law distributions with significantly different values, with the tail exponent falling between 0.5 and 0.7 for coins, and between 1.0 and 1.3 for tokens. We provide a rationale for this, based on a simple proportional growth with birth & death model previously employed to describe the size distribution of firms, cities, webpages, etc. We empirically validate the model and its main predictions, in terms of proportional growth (Gibrat's law) of the coins and tokens. Estimating the main parameters of the model, the theoretical predictions for the power-law exponents of coin and token distributions are in remarkable agreement with the empirical estimations, given the simplicity of the model. Our results clearly characterize coins as being "entrenched incumbents" and tokens as an "explosive immature ecosystem", largely due to massive and exuberant Initial Coin Offering activity in the token space. The theory predicts that the exponent for tokens should converge to 1 in the future, reflecting a more reasonable rate of new entrants associated with genuine technological innovations.