Anomaly Detection in Bitcoin Prices using DBSCAN Algorithm

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dc.contributor.authorDokuz, Ahmet
dc.contributor.authorÇelik, Mete
dc.contributor.authorEcemiş, Alper
dc.date.accessioned2024-11-07T13:19:01Z
dc.date.available2024-11-07T13:19:01Z
dc.date.issued2020
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractBlockchain is an emerging technology which is also behind the Bitcoin digital money. Daily bitcoin transactions are increasing due tothe popular and widespread investments. The increase of Bitcoin related datasets and this increased big dataset requires novelapproaches and methods to analyze using data mining techniques. In addition, fluctuations and anomalies in the bitcoin prices couldmean a great deal to economists and discovering anomalies in bitcoin prices is important. In this study, anomaly detection in Bitcoinprices is performed based on the change of Bitcoin price difference and the change of Bitcoin price difference in percentage withrespect to previous day using 8-years of Bitcoin price dataset of the period of 2012-2019. First, the dataset is pre-processed andunnecessary columns are deleted. Then, 2 different datasets are created by using daily bitcoin prices, i.e. bitcoin price differencedataset and bitcoin price difference in percentage dataset. After that, for detecting anomalous price changes, DBSCAN algorithm andstatistical method are used, and the performance of the algorithms are evaluated. The results show that the DBSCAN algorithm andstatistical method successfully detects anomalies in bitcoin prices for both of the datasets. However, the DBSCAN algorithm performsbetter than the statistical method which could detect anomalies even they are close to the normal daily price changes. Also, in thisstudy, bitcoin price difference dataset and bitcoin price difference in percentage dataset are compared and the differences of theresults for both datasets and their reasons are explained.
dc.identifier.doi10.31590/ejosat.araconf57
dc.identifier.endpage443
dc.identifier.issn2148-2683
dc.identifier.issueEjosat Özel Sayı 2020 (ARACONF)
dc.identifier.startpage436
dc.identifier.trdizinid366104
dc.identifier.urihttps://doi.org/10.31590/ejosat.araconf57
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/366104
dc.identifier.urihttps://hdl.handle.net/11480/12830
dc.identifier.volume0
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofAvrupa Bilim ve Teknoloji Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241107
dc.subjectBilgisayar Bilimleri
dc.subjectYazılım Mühendisliği
dc.subjectİşletme Finans
dc.titleAnomaly Detection in Bitcoin Prices using DBSCAN Algorithm
dc.typeArticle

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