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A cryptocurrency empirical study focused on evaluating their distribution functions

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dc.contributor.authorLópez Martín, Carmen
dc.contributor.authorArguedas Sanz, Raquel
dc.contributor.authorBenito Muela, Sonia
dc.date.accessioned2024-05-20T11:24:02Z
dc.date.available2024-05-20T11:24:02Z
dc.date.issued2022-02-14
dc.description.abstractThis paper thoroughly examines the statistical properties of cryptocurrency returns, particularly focusing on studying which is the best statistical distribution for fitting this type of data. The preliminary statistical study reveals (i) high volatility, (ii) an inverse leverage effect, (iii) skewed distributions and (iv) high kurtosis. To capture the nonnormal characteristics observed in cryptocurrency data, we verified the goodness of fit of a large set of distributions, both symmetric and skewed distributions such as skewed Student-t, skewed generalized t, skewed generalized error and the inverse hyperbolic sign distributions. The results show that the skewed distributions outperform normal and Student-t distributions in fitting cryptocurrency data, although there is no one skewed distribution that systematically better fits the data. In addition, we compare these distributions in terms of their ability to forecast the market risk of cryptocurrencies. In line with the results obtained in the statistical analysis, we find that the skewed distributions provide better risk estimates than the normal and Student-t distributions, both in short and long positions, with SGED being the distribution that provides better results.en
dc.description.versionversión final
dc.identifier.doihttps://doi.org/10.1016/j.iref.2022.02.021
dc.identifier.urihttps://hdl.handle.net/20.500.14468/11896
dc.journal.titleInternational Review of Economics and Finance
dc.journal.volume79 (2022)
dc.language.isoen
dc.publisherElsevier
dc.relation.centerFacultad de Ciencias Económicas y Empresariales
dc.relation.departmentEconomía de la Empresa y Contabilidad
dc.rightsAtribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subject.keywordscryptocurrencies
dc.subject.keywordsdistributions
dc.subject.keywordsskewness
dc.subject.keywordsfat tail
dc.subject.keywordsrisk management
dc.titleA cryptocurrency empirical study focused on evaluating their distribution functionses
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
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relation.isAuthorOfPublication5caf1cb0-3213-4235-ae2e-9dfe4bea1889
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relation.isAuthorOfPublication.latestForDiscoveryc97e2d29-4ce5-49e3-b864-9810ead93be6
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