Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/20856
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dc.contributor.authorGonzález, MDLO-
dc.contributor.authorJareño, F-
dc.contributor.authorSkinner, F-
dc.date.accessioned2020-05-19T15:13:34Z-
dc.date.available2020-05-19T15:13:34Z-
dc.date.issued2020-
dc.identifier.citationMathematicsen_US
dc.identifier.issn2227-7390-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/20856-
dc.description.abstractThis article examines the connectedness between Bitcoin returns and returns of ten additional cryptocurrencies for several frequencies: daily, weekly and monthly, over the period January 2015 – March 2020 using a NARDL (nonlinear autoregressive distributed lag) approach. We find important and positive interdependencies among cryptocurrencies and significant long-run relations among most of them. In addition, non-bitcoin cryptocurrency returns seem to react in the same way to positive and negative changes in Bitcoin returns, obtaining strong evidence of asymmetry in the short-run. Finally, our results show high persistence in the impact of both positive and negative changes in Bitcoin returns on most of the other cryptocurrencies returns. Thus, our model explains about 50% of the other cryptocurrencies returns with changes in Bitcoin returns.en_US
dc.description.sponsorshipSpanish Ministerio de Economía, Industria y Competitividad (ECO2017-89715-P).en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectBitcoinen_US
dc.subjectCryptocurrenciesen_US
dc.subjectNARDLen_US
dc.subjectConnectednessen_US
dc.titleNonlinear autoregressive distributed lag approach: an application on the connectedness between Bitcoin returns and the other ten most relevant cryptocurrencies returnsen_US
dc.typeArticleen_US
dc.relation.isPartOfMathematics-
pubs.publication-statusAccepted-
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