Toward Characterizing Blockchain-Based Cryptocurrencies for Highly Accurate Predictions

被引：70

作者：

Saad, Muhammad ^{[1
]}

Choi, Jinchun ^{[1
,3
]}

Nyang, DaeHun ^{[4
]}

Kim, Joongheon ^{[5
]}

Mohaisen, Aziz ^{[2
]}

机构：

[1] Univ Cent Florida, Dept Comp Sci, Orlando, FL 32816 USA

[2] Univ Cent Florida, Orlando, FL 32816 USA

[3] Inha Univ, Dept Comp Informat Sci, Incheon 22212, South Korea

[4] Inha Univ, Incheon 22212, South Korea

[5] Chung Ang Univ, Seoul 156756, South Korea

来源：

IEEE SYSTEMS JOURNAL | 2020年 / 14卷 / 01期

基金：

新加坡国家研究基金会;

关键词：

Bitcoin; Blockchain; Ethereum; prediction;

D O I：

10.1109/JSYST.2019.2927707

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：321 / 332

页数：12

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