 The crypto collapse chronicles: Decoding cryptocurrency exchange defaultsNiranjan Sapkota Journal of International Financial Markets, Institutions and Money, 2025, vol. 99, issue C Abstract: This research explores the factors contributing to the failure of cryptocurrency exchanges by analyzing a sample of 845 exchanges. Using logit and probit models, it identifies key variables affecting cryptocurrency exchange defaults. The results show that cryptocurrency exchanges that are centralized, located in countries with high transparency indices, and offer fewer peer cryptocurrencies are more likely to default. Additionally, exchanges that impose high withdrawal fees and have no restrictions on clients from the United States are also positively associated with defaults. Moreover, the absence of referral schemes and having lower ratings each contributes marginally to defaults. Machine learning (ML) models including random forest, support vector machine, stacked ensemble confirm the robustness and high predictability of cryptocurrency exchange defaults. Keywords: Cryptocurrency exchange; Defaults; Logit; Probit; Machine learning (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:intfin:v:99:y:2025:i:c:s1042443124001598 DOI: 10.1016/j.intfin.2024.102093 Access Statistics for this article Journal of International Financial Markets, Institutions and Money is currently edited by I. Mathur and C. J. Neely More articles in Journal of International Financial Markets, Institutions and Money from Elsevier |
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