Anomaly Detection in Bitcoin Prices using DBSCAN Algorithm
Küçük Resim Yok
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Blockchain 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.
Açıklama
Anahtar Kelimeler
Bilgisayar Bilimleri, Yazılım Mühendisliği, İşletme Finans
Kaynak
Avrupa Bilim ve Teknoloji Dergisi
WoS Q Değeri
Scopus Q Değeri
Cilt
0
Sayı
Ejosat Özel Sayı 2020 (ARACONF)
