Title

Towards Characterizing Blockchain-Based Cryptocurrencies For Highly-Accurate Predictions

Keywords

Bitcoin; Blockchain; modeling; prediction

Abstract

In 2017, the Blockchain-based crypto currency market witnessed enormous growth. Bitcoin, the leading crypto currency, reached all-time highs many times over the year leading to speculations to explain the trend in its growth. In this paper, we study Bitcoin and explore features in its network that explain its price hikes. We gather data and analyze user and network activity that highly impact Bitcoin price. We monitor the change in the activities over time and relate them to economic theories. We identify key network features that determine the demand and supply dynamics of a crypto currency. Finally, we use machine learning methods to construct models that predict Bitcoin price. Our regression model predicts Bitcoin price with 99.4% accuracy and 0.0113 root mean squared error (RMSE).

Publication Date

7-6-2018

Publication Title

INFOCOM 2018 - IEEE Conference on Computer Communications Workshops

Number of Pages

704-709

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/INFCOMW.2018.8406859

Socpus ID

85050684069 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85050684069

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