A tree augmented naive bayes-based methodology for classifying cryptocurrency trends

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dc.authoridDursun Delen / 0000-0001-8857-5148en_US
dc.authorscopusidDursun Delen / 55887961100
dc.authorwosidDursun Delen / AGA-9892-2022en_US
dc.contributor.authorDağ, Ali
dc.contributor.authorDağ, Aslı Z.
dc.contributor.authorAsilkalkan, Abdullah
dc.contributor.authorŞimşek, Serhat
dc.contributor.authorDelen, Dursun
dc.date.accessioned2023-01-26T12:34:05Z
dc.date.available2023-01-26T12:34:05Z
dc.date.issued2023en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractAs the popularity of blockchain technology and investor confidence in Bitcoin (BTC) increased in recent years, many individuals started making BTC and other cryptocurrency investments, in expectation of high returns. However, as recent market movements have shown, the lack of regulation and oversight makes it difficult to guard against high volatility and potentially significant losses in this sector. In this study, we propose a datadriven Tree Augmented Naive (TAN) Bayes methodology that can be used for identifying the most important factors (as well as their conditional, interdependent relationships) influencing BTC price movements. As the model is parsimonious without sacrificing accuracy, sensitivity, and specificity-as evident from the average accuracy value-the proposed methodology can be used in practice for making short-term investment decisions.en_US
dc.identifier.citationDag, A., Dag, A. Z., Asilkalkan, A., Simsek, S., & Delen, D. (2023). A Tree Augmented Naïve Bayes-based methodology for classifying cryptocurrency trends. Journal of Business Research, 156, 113522.en_US
dc.identifier.doi10.1016/j.jbusres.2022.113522en_US
dc.identifier.issn0148-2963en_US
dc.identifier.scopus2-s2.0-85144076470en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.jbusres.2022.113522
dc.identifier.uri1873-7978
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3843
dc.identifier.volume156en_US
dc.identifier.wosWOS:000898769800007en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorDelen, Dursun
dc.language.isoenen_US
dc.publisherELSEVIERen_US
dc.relation.ispartofJOURNAL OF BUSINESS RESEARCHen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPrice Predictionen_US
dc.subjectBitcoinen_US
dc.subjectCryptocurrencyen_US
dc.subjectBusiness Analyticsen_US
dc.subjectTree Augmented Na?ve Bayesen_US
dc.titleA tree augmented naive bayes-based methodology for classifying cryptocurrency trendsen_US
dc.typeArticleen_US

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