Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-4794
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dc.contributor.authorOsterrieder, Jörg-
dc.date.accessioned2019-03-09T10:53:36Z-
dc.date.available2019-03-09T10:53:36Z-
dc.date.issued2017-
dc.identifier.isbn978-94-6252-311-1de_CH
dc.identifier.issn2352-5428de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/15966-
dc.description.abstractCryptocurrencies became popular with the emergence of Bitcoin and have shown an unprecedented growth over the last few years. As of November 2016, more than 720 cryptocurrencies exist, with Bitcoin still being the most popular one. We show the statistical properties of the most important cryptocurrencies. We characterize their exchange rates versus the US Dollar by fitting parametric distributions to them, including the Student t distribution, the generalized hyperbolic distribution as well as the asymmetric normal inverse Gaussian and the asymmetric variance gamma distribution. Our findings show that cryptocurrencies exhibit strong non-normal characteristics, with standard heavy-tailed distributions such as the Student t distribution giving good descriptions of the data. This is the first study that looks at the parametric distribution of cryptocurreny returns. The results are important for investment and risk management purposes.de_CH
dc.language.isoende_CH
dc.publisherAtlantis Pressde_CH
dc.relation.ispartofseriesAdvances in Economics, Business and Management Research (AEBMR)de_CH
dc.rightshttp://creativecommons.org/licenses/by-nc/4.0/de_CH
dc.subjectHeavy-tailedde_CH
dc.subjectBitcoinde_CH
dc.subjectCryptocurrencyde_CH
dc.subjectStatisticsde_CH
dc.subject.ddc332: Finanzwirtschaftde_CH
dc.titleThe statistics of bitcoin and cryptocurrenciesde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.21256/zhaw-4794-
dc.identifier.doi10.2991/icefs-17.2017.33de_CH
zhaw.conference.details2017 International Conference on Economics, Finance and Statistics (ICEFS 2017), Hong Kong, 14-15 January 2017de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number26de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedings2017 International Conference on Economics, Finance and Statistics (ICEFS 2017)de_CH
Appears in Collections:Publikationen School of Engineering

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