Cross-exchange crypto risk: A high-frequency dynamic network perspective

Yifu Wang, Wanbo Lu, Min-Bin Lin, Rui Ren and Wolfgang Karl Härdle

International Review of Financial Analysis, 2024, vol. 94, issue C

Abstract: Cross-exchange crypto trading presents inherent risks, particularly for centralized exchanges. Investors observe exacerbating crypto volatility and counterparty risk and would like to quantify these elements of crypto trades. The multiple exchanges require a multivariate view on the structures of risk spillover across exchanges. Here, a Multivariate Heterogeneous AutoRegression (MHAR) model is designed and analyzed, accommodating the stylized facts of crypto markets, including 24/7 trading and the long-memory effect on return variations. The proposed MHAR approach clearly reveals the intensity of interconnectedness among exchanges during extreme events, e.g., the Bitcoin market. Additionally, one observes extremely volatile eigenvector centralities of Futures Exchange Ltd (FTX), suggesting potential implications for its bankruptcy. Furthermore, portfolios that account for the dynamics of partial correlations or eigenvector centralities offer promising results in terms of risk measures.

Keywords: Partial correlation network; High-frequency data; Bitcoin; FTX; HAR (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:94:y:2024:i:c:s1057521924001789

DOI: 10.1016/j.irfa.2024.103246

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