Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure

While there is increasing interest in crypto assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we considered a unique dataset of 144 exchanges, active from the first quarter of 2018 to the first quarter of 2021. We analyzed the determinants surrounding the...

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Autores principales:	Dean Fantazzini, Raffaella Calabrese
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	exchange Bitcoin crypto assets cryptocurrencies credit risk bankruptcy Risk in industry. Risk management HD61 Finance HG1-9999
Acceso en línea:	https://doaj.org/article/068c905f1a074ae9af9c1c73427947f9
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spelling	oai:doaj.org-article:068c905f1a074ae9af9c1c73427947f92021-11-25T18:08:30ZCrypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure10.3390/jrfm141105161911-80741911-8066https://doaj.org/article/068c905f1a074ae9af9c1c73427947f92021-10-01T00:00:00Zhttps://www.mdpi.com/1911-8074/14/11/516https://doaj.org/toc/1911-8066https://doaj.org/toc/1911-8074While there is increasing interest in crypto assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we considered a unique dataset of 144 exchanges, active from the first quarter of 2018 to the first quarter of 2021. We analyzed the determinants surrounding the decision to close an exchange using credit scoring and machine learning techniques. 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 analyzes confirm these findings. These results are robust in regard to the inclusion of additional variables, considering the country of registration of these exchanges and whether they are centralized or decentralized.Dean FantazziniRaffaella CalabreseMDPI AGarticleexchangeBitcoincrypto assetscryptocurrenciescredit riskbankruptcyRisk in industry. Risk managementHD61FinanceHG1-9999ENJournal of Risk and Financial Management, Vol 14, Iss 516, p 516 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	exchange Bitcoin crypto assets cryptocurrencies credit risk bankruptcy Risk in industry. Risk management HD61 Finance HG1-9999
spellingShingle	exchange Bitcoin crypto assets cryptocurrencies credit risk bankruptcy Risk in industry. Risk management HD61 Finance HG1-9999 Dean Fantazzini Raffaella Calabrese Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure
description	While there is increasing interest in crypto assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we considered a unique dataset of 144 exchanges, active from the first quarter of 2018 to the first quarter of 2021. We analyzed the determinants surrounding the decision to close an exchange using credit scoring and machine learning techniques. 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 analyzes confirm these findings. These results are robust in regard to the inclusion of additional variables, considering the country of registration of these exchanges and whether they are centralized or decentralized.
format	article
author	Dean Fantazzini Raffaella Calabrese
author_facet	Dean Fantazzini Raffaella Calabrese
author_sort	Dean Fantazzini
title	Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure
title_short	Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure
title_full	Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure
title_fullStr	Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure
title_full_unstemmed	Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure
title_sort	crypto exchanges and credit risk: modeling and forecasting the probability of closure
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/068c905f1a074ae9af9c1c73427947f9
work_keys_str_mv	AT deanfantazzini cryptoexchangesandcreditriskmodelingandforecastingtheprobabilityofclosure AT raffaellacalabrese cryptoexchangesandcreditriskmodelingandforecastingtheprobabilityofclosure
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Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure

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