Information Flow in the FTX Bankruptcy: A Network Approach

Paper: arXiv 2407.12683

Abstract

This paper investigates the cryptocurrency network of the FTX exchange during the collapse of its native token, FTT, to understand how network structures adapt to significant financial disruptions, by exploiting vertex centrality measures. Using proprietary data on the transactional relationships between various cryptocurrencies, we construct the filtered correlation matrix to identify the most significant relations in the FTX and Binance markets. By using suitable centrality measures - closeness and information centrality - we assess network stability during FTX’s bankruptcy. The findings document the appropriateness of such vertex centralities in understanding the resilience and vulnerabilities of financial networks. By tracking the changes in centrality values before and during the FTX crisis, this study provides useful insights into the structural dynamics of the cryptocurrency market. Results reveal how different cryptocurrencies experienced shifts in their network roles due to the crisis. Moreover, our findings highlight the interconnectedness of cryptocurrency markets and how the failure of a single entity can lead to widespread repercussions that destabilize other nodes of the network.

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 8.0/10
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper employs advanced network mathematics like centrality measures (closeness, information) and filtered correlation matrices, reflecting high mathematical complexity, and uses proprietary transactional data with time-series analysis and network construction methods, indicating strong empirical rigor.

Research Flowchart

  flowchart TD
  A["Research Goal:<br>How does FTX collapse impact<br>cryptocurrency network structure?"] --> B["Input Data:<br>Transactional relationships between<br>cryptocurrencies in FTX/Binance markets"]
  B --> C["Methodology:<br>Construct Filtered Correlation Matrix<br>to identify significant relations"]
  C --> D["Computation:<br>Calculate Vertex Centrality Measures<br>(Closeness & Information Centrality)"]
  D --> E{"Analysis Period"}
  E -->|Pre-Crisis| F["Establish Baseline Network Stability"]
  E -->|During Crisis| G["Assess Network Adaptation & Vulnerability"]
  F --> H["Key Findings:<br>1. Centrality measures effectively gauge systemic risk<br>2. Crypto markets are highly interconnected<br>3. Single entity failure causes widespread destabilization<br>4. Cryptocurrencies shift network roles during crises"]
  G --> H

Cited References (84)

1. Analysis of cryptocurrency transactions from a network perspective: An overview (2021) — link
2. Cross-exchange crypto risk: A high-frequency dynamic network perspective (2024) — link
3. FTX ’s downfall and Binance ’s consolidation: The fragility of centralised digital finance (2023) — link
4. Short Paper : A Centrality Analysis of the Lightning Network (2022) — link
5. Extreme tail network analysis of cryptocurrencies and trading strategies (2022) — link
6. Pairwise and high-order dependencies in the cryptocurrency trading network (2022) — link
7. The cryptocurrency market: A network analysis (2018) — link
8. A network analysis of electricity demand and the cryptocurrency markets (2021) — link

0 of 84 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.