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The crypto collapse chronicles: Decoding cryptocurrency exchange defaults

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  • Sapkota, Niranjan

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.

Suggested Citation

  • Sapkota, Niranjan, 2025. "The crypto collapse chronicles: Decoding cryptocurrency exchange defaults," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 99(C).
    • Handle: RePEc:eee:intfin:v:99:y:2025:i:c:s1042443124001598
    DOI: 10.1016/j.intfin.2024.102093
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    More about this item

    Keywords

    Cryptocurrency exchange; Defaults; Logit; Probit; Machine learning;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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