Digital Currency Price Analysis Via Deep Forecasting Approaches for Business Risk Mitigation

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dc.authoridVarol, Asaf/0000-0003-1606-4079en_US
dc.authoridRaza, Muhammad Raheel/0000-0002-6305-2583en_US
dc.contributor.authorRaza, Muhammad Raheel
dc.contributor.authorVarol, Asaf
dc.date.accessioned2024-07-12T21:40:38Z
dc.date.available2024-07-12T21:40:38Z
dc.date.issued2021en_US
dc.department[Belirlenecek]en_US
dc.description2nd International Informatics and Software Engineering Conference (IISEC) - Artificial Intelligence for Digital Transformation -- DEC 16-17, 2021 -- Ankara, TURKEYen_US
dc.description.abstractBitcoin, the most well-known of all the cryptocurrencies, have attracted a lot of attention thus far, and their prices have been quite volatile. While some research employ traditional statistical and econometric methods to discover the factors that drive Bitcoin prices, experimenting on the development of prediction models to be utilized as decision support aids in investment approaches is uncommon. The sudden rise and fall of cryptocurrency rates affects the economies and future perspectives of various businesses. In order to minimize business risks, to track the differences and avoid serious economic loss, prediction of daily digital currency rates becomes a crucial task. Our study performs a comparative analysis of Bitcoin price prediction utilizing efficient neural network techniques such as LSTM and GRU. A better RNN-based approach is derived as a result of the study. This approach will assist to facilitate a secure environment for businesses and to alarms to carryout risk management tasks for business risk mitigation purposes.en_US
dc.description.sponsorshipIEEE Turkey Secten_US
dc.identifier.doi10.1109/IISEC54230.2021.9672381
dc.identifier.isbn978-1-6654-0759-5
dc.identifier.scopus2-s2.0-85125346834en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/IISEC54230.2021.9672381
dc.identifier.urihttps://hdl.handle.net/20.500.12415/7400
dc.identifier.wosWOS:000841548300023en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2nd International Informatics And Software Engineering Conference (Iisec)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKY08741
dc.subjectBitcoinen_US
dc.subjectCryptocurrencyen_US
dc.subjectDigital Currencyen_US
dc.subjectPrice Predictionen_US
dc.subjectDeep Learningen_US
dc.subjectForecastingen_US
dc.subjectLstmen_US
dc.subjectGruen_US
dc.subjectBusiness Risken_US
dc.subjectRisk Managementen_US
dc.subjectInformation Securityen_US
dc.titleDigital Currency Price Analysis Via Deep Forecasting Approaches for Business Risk Mitigationen_US
dc.typeConference Object
dspace.entity.typePublication

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