Token Composition: A Graph Based on EVM Logs

TL;DR

An empirical analysis of token composition on the Ethereum blockchain is performed, introducing a graph that represents the tokenisation of tokens by other tokens, and it is shown that the graph contains non-trivial topological structure.

Abstract

Tokens have proliferated across blockchains in terms of number, market capitalisation and utility. Some tokens are tokenised versions of existing tokens -- known variously as wrapped tokens, fractional tokens, or shares. The repeated application of this process creates matryoshkian tokens of arbitrary depth. We perform an empirical analysis of token composition on the Ethereum blockchain. We introduce a graph that represents the tokenisation of tokens by other tokens, and we show that the graph contains non-trivial topological structure. We relate properties of the graph, e.g., connected components and cyclic structure, to the tokenisation process. For example, we identify the longest directed path and its corresponding sequence of tokens, and we visualise the connected components relating to a stablecoin and an NFT protocol. Our goal is to explore and visualise what has been wrought with tokens, rather than add yet another brick to the edifice.

Figures (7)

• Figure 1: Tokens can have many layers of composition. For example, one can: stakeETH for eETH to earn yield; wrapeETH for weETH to collect the yield; wrapweETH for SY-weETH to standardise the yield collection mechanism; and splitSY-weETH into PT-weETH and YT-weETH to separate the principal from the yield up to a maturity.
• Figure 2: A token graph, $\mathcal{TG}$, with eight vertices, $t_0, t_1, \ldots, t_7$, and eight edges. Each edge corresponds to a token tokenising another token. For example, the token represented by $t_5$ tokenises the token represented by $t_0$.
• Figure 3: The in- and out-degree distributions of the unfiltered token graph show an inverse relationship between the degree of a vertex and the number of vertices with that degree. There are a small number of vertices with high degree and a large number of vertices with low degree.
• Figure 4: The in- and out-degree distributions of the filtered token graph show a similar inverse relationship as in Fig. \ref{['fig:unfiltered-token-graph-degrees']}.
• Figure 5: In the unfiltered and filtered token graphs, we can identify vertices with both high in-degree and high out-degree.