The Determinants of Bitcoin’s Price: Utilization of GARCH and Machine Learning Approaches

Ting Hsuan Chen, Mu Yen Chen, Guan Ting Du

研究成果: Article同行評審

12 引文 斯高帕斯(Scopus)

摘要

This study explores the determinants of Bitcoin’s price from 2010 to 2018. This study applies Generalized Autoregressive Conditional Heteroskedastic model to investigate the Bitcoin datasets. The experimental results find the Bitcoin price has positive relationship to the exchange rates (USD/Euro, USD/GBP, USD/CHF and Euro/GBP), the DAX and the Nikkei 225, while a negative relationship with the Fed funds rate, the FTSE 100, and the USD index. Especially, Bitcoin price is significantly affected by the Fed funds rate, followed by the Euro/GBP rate, the USD/GBP rate and the West Texas Intermediate price. This study also executes the decision tree and support vector machine techniques to predict the trend of Bitcoin price. The machine learning approach could be a more suitable methodology than traditional statistics for predicting the Bitcoin price.

原文English
頁(從 - 到)267-280
頁數14
期刊Computational Economics
57
發行號1
DOIs
出版狀態Published - 2021 1月

All Science Journal Classification (ASJC) codes

  • 經濟學、計量經濟學和金融學(雜項)
  • 電腦科學應用

指紋

深入研究「The Determinants of Bitcoin’s Price: Utilization of GARCH and Machine Learning Approaches」主題。共同形成了獨特的指紋。

引用此