Crypto-exchanges and Credit Risk: Modelling and Forecasting the Probability of Closure

Dean Fantazzini and Raffaella Calabrese

MPRA Paper from University Library of Munich, Germany

Abstract: While there is an increasing interest in crypto-assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we consider a unique data set on 144 exchanges active from the first quarter of 2018 to the first quarter of 2021. We analyze the determinants of the decision of closing an exchange using credit scoring and machine learning techniques. The cybersecurity grades, having a public developer team, the age of the exchange, and the number of available traded cryptocurrencies are the main significant covariates across different model specifications. Both in-sample and out-of-sample analyses confirm these findings. These results are robust to the inclusion of additional variables considering the country of registration of these exchanges and whether they are centralized or decentralized.

Keywords: Exchange; Bitcoin; Crypto-assets; Crypto-currencies; Credit risk; Bankruptcy; Default Probability (search for similar items in EconPapers)
JEL-codes: C21 C35 C51 C53 G23 G32 G33 (search for similar items in EconPapers)
Date: 2021
New Economics Papers: this item is included in nep-ban, nep-big, nep-cfn, nep-fdg, nep-fmk, nep-ore, nep-pay and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Journal Article: Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:110391

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