Analysis of ego multi-token transfer networks: a multilayer approach

Célestin Coquidé; Rémy Cazabet; Natkamon Tovanich

doi:10.1007/s41109-025-00712-z

Analysis of ego multi-token transfer networks: a multilayer approach

Célestin Coquidé
, Rémy Cazabet
, Natkamon Tovanich

Université de Lyon

Research output: Contribution to journal › Article › peer-review

Abstract

This study introduces the Multilayer Token Network (MLTN), a mathematical framework for analyzing Ethereum token transfers while capturing inter-token transformations crucial to Decentralized Finance (DeFi). Focusing on prominent fund accounts, we propose the PageRank-CheiRank Trade Balance (PCTB), an econometric measure inspired by balance sheet principles to quantify trade behavior over time. Applying MLTN to 2018–2024 transaction data, we reveal Alameda Research’s evolving trade strategies, fund interdependencies, and token-specific accumulation and distribution patterns, offering new insights into on-chain financial activities.

Original language	English
Article number	37
Journal	Applied Network Science
Volume	10
Issue number	1
DOIs	https://doi.org/10.1007/s41109-025-00712-z
Publication status	Published - 1 Dec 2025

Keywords

Blockchain analytics
Cryptocurrency network
Ethereum
Multilayer network
PageRank centrality
Token transfer network

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10.1007/s41109-025-00712-z

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title = "Analysis of ego multi-token transfer networks: a multilayer approach",

abstract = "This study introduces the Multilayer Token Network (MLTN), a mathematical framework for analyzing Ethereum token transfers while capturing inter-token transformations crucial to Decentralized Finance (DeFi). Focusing on prominent fund accounts, we propose the PageRank-CheiRank Trade Balance (PCTB), an econometric measure inspired by balance sheet principles to quantify trade behavior over time. Applying MLTN to 2018–2024 transaction data, we reveal Alameda Research{\textquoteright}s evolving trade strategies, fund interdependencies, and token-specific accumulation and distribution patterns, offering new insights into on-chain financial activities.",

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AU - Coquidé, Célestin

AU - Cazabet, Rémy

AU - Tovanich, Natkamon

N1 - Publisher Copyright: © The Author(s) 2025.

PY - 2025/12/1

Y1 - 2025/12/1

N2 - This study introduces the Multilayer Token Network (MLTN), a mathematical framework for analyzing Ethereum token transfers while capturing inter-token transformations crucial to Decentralized Finance (DeFi). Focusing on prominent fund accounts, we propose the PageRank-CheiRank Trade Balance (PCTB), an econometric measure inspired by balance sheet principles to quantify trade behavior over time. Applying MLTN to 2018–2024 transaction data, we reveal Alameda Research’s evolving trade strategies, fund interdependencies, and token-specific accumulation and distribution patterns, offering new insights into on-chain financial activities.

AB - This study introduces the Multilayer Token Network (MLTN), a mathematical framework for analyzing Ethereum token transfers while capturing inter-token transformations crucial to Decentralized Finance (DeFi). Focusing on prominent fund accounts, we propose the PageRank-CheiRank Trade Balance (PCTB), an econometric measure inspired by balance sheet principles to quantify trade behavior over time. Applying MLTN to 2018–2024 transaction data, we reveal Alameda Research’s evolving trade strategies, fund interdependencies, and token-specific accumulation and distribution patterns, offering new insights into on-chain financial activities.

KW - Blockchain analytics

KW - Cryptocurrency network

KW - Ethereum

KW - Multilayer network

KW - PageRank centrality

KW - Token transfer network

UR - https://www.scopus.com/pages/publications/105014603262

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DO - 10.1007/s41109-025-00712-z

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AN - SCOPUS:105014603262

SN - 2364-8228

VL - 10

JO - Applied Network Science

JF - Applied Network Science

IS - 1

M1 - 37

ER -

Analysis of ego multi-token transfer networks: a multilayer approach

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