Information flow in the FTX bankruptcy: A network approach

IF 2.8 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Riccardo De Blasis , Luca Galati , Rosanna Grassi , Giorgio Rizzini
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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.
FTX 破产案中的信息流:网络方法
本文研究了 FTX 交易所在其原生代币 FTT 崩溃期间的加密货币网络,通过利用顶点中心性度量来了解网络结构如何适应重大金融干扰。利用各种加密货币之间交易关系的专有数据,我们构建了过滤相关矩阵,以识别 FTX 和 Binance 市场中最重要的关系。通过使用合适的中心性度量--紧密性和信息中心性--我们评估了 FTX 破产期间的网络稳定性。研究结果证明,这种顶点中心性适合用于理解金融网络的弹性和脆弱性。通过跟踪 FTX 危机前和危机期间中心性值的变化,本研究为了解加密货币市场的结构动态提供了有用的见解。研究结果揭示了不同加密货币的网络角色是如何因危机而发生转变的。此外,我们的研究结果还凸显了加密货币市场的相互关联性,以及单一实体的失败如何导致广泛的影响,从而破坏网络中其他节点的稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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