Toward characterizing blockchain-based cryptocurrencies for highly accurate predictions

Muhammad Saad, Jinchun Choi, Daehun Nyang, Joongheon Kim, Aziz Mohaisen

Research output: Contribution to journalArticlepeer-review

44 Scopus citations


Recently, the Blockchain-based cryptocurrency market witnessed enormous growth. Bitcoin, the leading cryptocurrency, reached all-time highs many times over the year leading to speculations to explain the trend in its growth. In this article, we study Bitcoin and Ethereum and explore features in their network that explain their price hikes. We gather data and analyze user and network activity that highly impact the price of these cryptocurrencies. We monitor the change in the activities over time and relate them to economic theories. We identify key network features that help us to determine the demand and supply dynamics in a cryptocurrency. Finally, we use machine learning methods to construct models that predict Bitcoin price. Based on our experimental results using two large datasets for validation, we confirm that our approach provides an accuracy of up to 99% for Bitcoin and Ethereum price prediction in both instances.

Original languageEnglish
Article number8840919
Pages (from-to)321-332
Number of pages12
JournalIEEE Systems Journal
Issue number1
StatePublished - Mar 2020


  • Bitcoin
  • Blockchain
  • Ethereum
  • Prediction


Dive into the research topics of 'Toward characterizing blockchain-based cryptocurrencies for highly accurate predictions'. Together they form a unique fingerprint.

Cite this