Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-4793
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dc.contributor.authorChan, Stephen-
dc.contributor.authorChu, Jeffrey-
dc.contributor.authorNadarajah, Saralees-
dc.contributor.authorOsterrieder, Jörg-
dc.date.accessioned2019-03-08T14:12:39Z-
dc.date.available2019-03-08T14:12:39Z-
dc.date.issued2017-
dc.identifier.issn1911-8066de_CH
dc.identifier.issn1911-8074de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/15943-
dc.description.abstractWe analyze statistical properties of the largest cryptocurrencies (determined by market capitalization), of which Bitcoin is the most prominent example. We characterize their exchange rates versus the US Dollar by fitting parametric distributions to them. It is shown that returns are clearly non-normal, however, no single distribution fits well jointly to all the cryptocurrencies analysed. We find that for the most popular currencies, such as Bitcoin and Litecoin, the generalized hyperbolic distribution gives the best fit, whilst for the smaller cryptocurrencies the normal inverse Gaussian distribution, generalized t distribution, and Laplace distribution give good fits. The results are important for investment and risk management purposes.de_CH
dc.language.isoende_CH
dc.publisherMDPIde_CH
dc.relation.ispartofJournal of Risk and Financial Managementde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectFintechde_CH
dc.subjectBitcoinde_CH
dc.subjectExchange ratesde_CH
dc.subjectCryptocurrenciesde_CH
dc.subject.ddc332: Finanzwirtschaftde_CH
dc.titleA statistical analysis of cryptocurrenciesde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.21256/zhaw-4793-
dc.identifier.doi10.3390/jrfm10020012de_CH
zhaw.funding.euNode_CH
zhaw.issue12de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume10de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedFinTechde_CH
Appears in collections:Publikationen School of Engineering

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