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dc.contributor.authorDahham, Ahmed Zahim Dahham
dc.contributor.authorIbrahim, Abdullahi Abdu
dc.date.accessioned2021-05-15T12:49:30Z
dc.date.available2021-05-15T12:49:30Z
dc.date.issued2020
dc.identifier.issn1757-8981
dc.identifier.urihttps://doi.org/10.1088/1757-899X/928/3/032043
dc.identifier.urihttps://hdl.handle.net/20.500.12939/1035
dc.description2nd International Scientific Conference of Al-Ayen University, ISCAU 2020 -- 15 July 2020 through 17 July 2020 -- -- 165187en_US
dc.description2-s2.0-85097154640en_US
dc.description.abstractThe purpose of this research is to identify how effective the determinants of the improved price changes in cryptocurrencies are and if they are predictable. The study addresses several independent variables that are in our consideration which may impact the prices the most. To obtain the results, panel data has been used to run fixed effects models. Then we treated them as time series data to run dynamic trend indicator and first-differencing volatility regression model. Important political shocks and instabilities have been analyzed and interpreted in this paper. In the light of our findings we were able to comment on the complex relation between cryptocurrency prices and socio-political situations throughout the time range. The results address that cryptocurrency price changes are predictable. It is easy to say that major stakeholders (Apple, Amazon, Facebook, Google, Tesla) affect the most prices. Internet search trends seem to have an impact but at the end it has been found that the correlation is strong. We have evaluated all the major cryptocurrency prices with exact accuracy of 95.38% using the volatility regression model effectively. All the cryptocurrencies are evaluated against US dollars in regard of different cryptocurrency like Bitcoin, Ethereum, Litecoin and Ripple digital currency. Cryptocurrencies shouldn't be seen as a gambling medium and should be taken more seriously like an investment medium. In some specific occasions investing in cryptocurrencies may lead lucrative income. © 2020 Published under licence by IOP Publishing Ltd.en_US
dc.language.isoengen_US
dc.publisherIOP Publishing Ltden_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBitcoinen_US
dc.subjectCryptocurrencyen_US
dc.subjectGovernmenten_US
dc.subjectPredictionen_US
dc.subjectRegression Modelen_US
dc.subjectTrend Indicatoren_US
dc.subjectVolatilityen_US
dc.titleEffects of volatility and trend indicator for improving price prediction of cryptocurrencyen_US
dc.typeconferenceObjecten_US
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Elektrik ve Bilgisayar Mühendisliği Bölümüen_US
dc.department-tempDahham, A.Z.D., Information Technology, Altinbas University, Istanbul, Turkey; Ibrahim, A.A., Electrical and Computer Engineering, Altinbas University, Istanbul, Turkeyen_US
dc.contributor.institutionauthorIbrahim, Abdullahi Abdu
dc.contributor.institutionauthorDahham, Ahmed Zahim Dahham
dc.identifier.doi10.1088/1757-899X/928/3/032043
dc.identifier.volume928en_US
dc.identifier.issue3en_US
dc.relation.journalIOP Conference Series: Materials Science and Engineeringen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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