EconPapers    
Economics at your fingertips  
 

Clustering Uniswap v3 traders from their activity on multiple liquidity pools, via novel graph embeddings

Deborah Miori () and Mihai Cucuringu
Additional contact information
Deborah Miori: University of Oxford
Mihai Cucuringu: University of Oxford

Digital Finance, 2024, vol. 6, issue 1, No 6, 113-143

Abstract: Abstract Uniswap is a Constant Product Market Maker built around liquidity pools, where pairs of tokens are exchanged subject to a fee that is proportional to the size of transactions. At the time of writing, there exist more than 6000 pools associated with Uniswap v3, implying that empirical investigations on the full ecosystem can easily become computationally expensive. We propose a systematic workflow to extract a tractable sub-universe of liquidity pools, where the interconnection among such pools is maximised to capture broader dynamics within the ecosystem. The resultant set of 34 pools is then used to cluster market participants according to their liquidity consumption behaviour over such environments, for the time window January–June 2022. Introducing a novel approach, we proceed to represent each liquidity taker by a suitably constructed transaction graph. The graph is a fully connected network where nodes are the liquidity taker’s executed transactions on the 34 pools of reference, and edges contain weights encoding the time elapsed between any two transactions. We then extend the NLP-inspired graph2vec algorithm to the weighted undirected setting, and employ it to obtain an embedding of the set of graphs representing market participants. This embedding allows us to extract seven clusters of liquidity takers, with equivalent behavioural patterns that can be interpreted in terms of trading attributes, i.e. preference for exotic assets over stablecoins, frequency of activity, tolerance for higher trading fees.

Keywords: Clustering; Decentralised finance; Network analysis; NLP; Uniswap v3 (search for similar items in EconPapers)
JEL-codes: C0 C6 C8 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s42521-024-00105-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:digfin:v:6:y:2024:i:1:d:10.1007_s42521-024-00105-4

Ordering information: This journal article can be ordered from
https://www.springer.com/finance/journal/42521

DOI: 10.1007/s42521-024-00105-4

Access Statistics for this article

Digital Finance is currently edited by Wolfgang Karl Härdle, Steven Kou and Min Dai

More articles in Digital Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-12
Handle: RePEc:spr:digfin:v:6:y:2024:i:1:d:10.1007_s42521-024-00105-4