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Inside Alameda Research: A Multi-Token Network Analysis

Célestin Coquidé, Rémy Cazabet, Natkamon Tovanich

TL;DR

The temporal evolution of Alameda accounts reveals shifts in token accumulation and distribution patterns leading up to its bankruptcy in November 2022, offering insights into the activities and dynamics that shape the DeFi ecosystem.

Abstract

We analyze the token transfer network on Ethereum, focusing on accounts associated with Alameda Research, a cryptocurrency trading firm implicated in the misuse of FTX customer funds. Using a multi-token network representation, we examine node centralities and the network backbone to identify critical accounts, tokens, and activity groups. The temporal evolution of Alameda accounts reveals shifts in token accumulation and distribution patterns leading up to its bankruptcy in November 2022. Through network analysis, our work offers insights into the activities and dynamics that shape the DeFi ecosystem.

Inside Alameda Research: A Multi-Token Network Analysis

TL;DR

The temporal evolution of Alameda accounts reveals shifts in token accumulation and distribution patterns leading up to its bankruptcy in November 2022, offering insights into the activities and dynamics that shape the DeFi ecosystem.

Abstract

We analyze the token transfer network on Ethereum, focusing on accounts associated with Alameda Research, a cryptocurrency trading firm implicated in the misuse of FTX customer funds. Using a multi-token network representation, we examine node centralities and the network backbone to identify critical accounts, tokens, and activity groups. The temporal evolution of Alameda accounts reveals shifts in token accumulation and distribution patterns leading up to its bankruptcy in November 2022. Through network analysis, our work offers insights into the activities and dynamics that shape the DeFi ecosystem.
Paper Structure (18 sections, 8 equations, 5 figures, 1 table)

This paper contains 18 sections, 8 equations, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Dataset
  4. List of fund accounts:
  5. Token transfer data:
  6. Labeled addresses
  7. Filtering out spam tokens
  8. Ego Multi-Token Network
  9. Network construction
  10. Backbone extraction
  11. User and token centrality measures
  12. PageRank and token accumulators.
  13. CheiRank and token spreader.
  14. PageRank-CheiRank trade balance
  15. Results
  16. ...and 3 more sections

Figures (5)

  • Figure 1: Node degree cumulative distribution regarding incoming (orange) and outgoing (blue) edges for (a) the global multi-token network, and (b) its largest SCC. (c) Diameter distribution for SCCs.
  • Figure 2: Top-10 users and tokens regarding PageRank and CheiRank scores
  • Figure 3: Visualization of the backbone network. Node color represents each cluster, while node size is proportional to the PageRank score. Link thickness corresponds to the number of transactions between nodes.
  • Figure 4: Evolution of snapshot sizes and compositions: (a) number of nodes (blue) and edges (orange), (b) percentage of new users (blue) and new tokens (orange), and (c) number of edges (orange) and transactions (blue) Alameda is involved. Yearly (solid lines), monthly (dashed lines) and daily (dotted lines).
  • Figure 5: Temporal evolution of Alameda Research's centralities of (a) PageRank and CheiRank scores, (b) PageRank-CheiRank Trade Balance scores for Alameda Research compared to all fund accounts, and (c) balance scores for the top-10 tokens for Alameda Research. Snapshots with month resolution are considered.