Predicting cryptocurrency defaults

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annif.suggestionselectronic money|virtual currency|currency|Internet|financial markets|foreign exchange market|means of payment|money (means of payment)|blockchains|Finland|enen
annif.suggestions.linkshttp://www.yso.fi/onto/yso/p3653|http://www.yso.fi/onto/yso/p28873|http://www.yso.fi/onto/yso/p3573|http://www.yso.fi/onto/yso/p20405|http://www.yso.fi/onto/yso/p7536|http://www.yso.fi/onto/yso/p18381|http://www.yso.fi/onto/yso/p8753|http://www.yso.fi/onto/yso/p3574|http://www.yso.fi/onto/yso/p38227|http://www.yso.fi/onto/yso/p94426en
dc.contributor.authorGrobys, Klaus
dc.contributor.authorSapkota, Niranjan
dc.contributor.departmentDigital Economy-
dc.contributor.facultyfi=Laskentatoimen ja rahoituksen yksikkö|en=School of Accounting and Finance|-
dc.contributor.orcidhttps://orcid.org/0000-0002-4121-3606-
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2020-12-09T07:34:52Z
dc.date.accessioned2025-06-25T12:45:24Z
dc.date.available2021-11-03T01:00:29Z
dc.date.issued2020-05-03
dc.description.abstractWe examine all available 146 Proof-of-Work-based cryptocurrencies that started trading prior to the end of 2014 and track their performance until December 2018. We find that about 60% of those cryptocurrencies were eventually in default. The substantial sums of money involved mean those bankruptcies will have an enormous societal impact. Employing cryptocurrency-specific data, we estimate a model based on linear discriminant analysis to predict such defaults. Our model is capable of explaining 87% of cryptocurrency bankruptcies after only one month of trading and could serve as a screening tool for investors keen to boost overall portfolio performance and avoid investing in unreliable cryptocurrencies.-
dc.description.notification© 2020 Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis in Applied Economics Letters on 03 May 2020, available online: http://www.tandfonline.com/10.1080/00036846.2020.1752903-
dc.description.reviewstatusfi=vertaisarvioitu|en=peerReviewed|-
dc.embargo.lift2021-11-03
dc.embargo.terms2021-11-03
dc.format.bitstreamtrue
dc.format.contentfi=kokoteksti|en=fulltext|-
dc.format.extent17-
dc.format.pagerange5060-5076-
dc.identifier.olddbid13136
dc.identifier.oldhandle10024/11740
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/852
dc.identifier.urnURN:NBN:fi-fe2020120999953-
dc.language.isoeng-
dc.publisherTaylor & Francis-
dc.relation.doi10.1080/00036846.2020.1752903-
dc.relation.ispartofjournalApplied Economics-
dc.relation.issn1466-4283-
dc.relation.issn0003-6846-
dc.relation.issue46-
dc.relation.urlhttps://doi.org/10.1080/00036846.2020.1752903-
dc.relation.volume52-
dc.source.identifierWOS: 000538587300001-
dc.source.identifierScopus: 85084310713-
dc.source.identifierhttps://osuva.uwasa.fi/handle/10024/11740
dc.subjectCryptocurrency-
dc.subjectbitcoin-
dc.subjectbankruptcy-
dc.subjectdefault-
dc.subjectcredit risk-
dc.subject.disciplinefi=Laskentatoimi ja rahoitus|en=Accounting and Finance|-
dc.titlePredicting cryptocurrency defaults-
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|en=A1 Peer-reviewed original journal article|sv=A1 Originalartikel i en vetenskaplig tidskrift|-
dc.type.publicationarticle-
dc.type.versionacceptedVersion-

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