Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/30682
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dc.contributor.authorKing, Juan C.-
dc.contributor.authorDale, Roberto-
dc.contributor.authorAMIGO, JOSE M.-
dc.contributor.otherDepartamentos de la UMH::Estadística, Matemáticas e Informáticaes_ES
dc.date.accessioned2024-01-26T09:54:32Z-
dc.date.available2024-01-26T09:54:32Z-
dc.date.created2023-11-22-
dc.identifier.citationChaos, Solitons and Fractals, vol. 178, 2024, 114305es_ES
dc.identifier.issn1873-2887-
dc.identifier.issn0960-0779-
dc.identifier.urihttps://hdl.handle.net/11000/30682-
dc.description.abstractThe objective of this paper is the construction of new indicators that can be useful to operate in the cryptocurrency market. These indicators are based on public data obtained from the blockchain network, specifically from the nodes that make up Bitcoin mining. Therefore, our analysis is unique to that network. The results obtained with numerical simulations of algorithmic trading and prediction via statistical models and Machine Learning demonstrate the importance of variables such as the hash rate, the difficulty of mining or the cost per transaction when it comes to trade Bitcoin assets or predict the direction of price. Variables obtained from the blockchain network will be called here blockchain metrics. The corresponding indicators (inspired by the ‘‘Hash Ribbon’’) perform well in locating buy signals. From our results, we conclude that such blockchain indicators allow obtaining information with a statistical advantage in the highly volatile cryptocurrency market.es_ES
dc.formatapplication/pdfes_ES
dc.format.extent15es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectTime serieses_ES
dc.subjectBlockchaines_ES
dc.subjectBitcoines_ES
dc.subjectCryptocurrencyes_ES
dc.subjectHash ribbones_ES
dc.subjectHash ratees_ES
dc.subjectAlgorithmic tradinges_ES
dc.subjectPredictiones_ES
dc.subjectMachine learninges_ES
dc.subjectAdaptive marketses_ES
dc.subjectFundamental analysises_ES
dc.subjectTechnical analysises_ES
dc.subjectMathematical indicatorses_ES
dc.subject.classificationLenguajes y sistemas informaticoses_ES
dc.subject.otherCDU::5 - Ciencias puras y naturales::51 - Matemáticases_ES
dc.titleBlockchain metrics and indicators in cryptocurrency tradinges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.chaos.2023.114305es_ES
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Artículos Estadística, Matemáticas e Informática


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