A tree augmented naive bayes-based methodology for classifying cryptocurrency trends
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Tarih
2023
Dergi Başlığı
Dergi ISSN
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Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
As 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.
Açıklama
Anahtar Kelimeler
Price Prediction, Bitcoin, Cryptocurrency, Business Analytics, Tree Augmented Na?ve Bayes
Kaynak
JOURNAL OF BUSINESS RESEARCH
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
156
Sayı
Künye
Dag, 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.
