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Predicting Ethereum Prices using Machine Learning and Block Chain Information

By Han-Min Kim, Gee-Woo Bock and Gunwoong Lee

Abstract

With the growing interest in cryptocurrency and its algorithm, studies on cryptocurrency price predations have been extensively conducted in various academic disciplines. Since the cryptocurrency is generated and consumed by the Blockchain system, it has been considered that Blockchain-specific information would be the main components in predicting cryptocurrency prices. Specifically, this point of view has been largely employed in the studies of Bitcoin price predictions. However, this study recognizes that Ethereum, a popular and leading cryptocurrency in the market, has distinct Blockchain information as compared to that of Bitcoin. We attempt to investigate the relationships between inherent Ethereum Blockchain information and Ethereum prices. Furthermore, the research examines how Blockchain information of other coins in the market is associated with Ethereum prices. The results of data analysis show that Ethereum Blockchain information and Blockchain information of other coins have strong correlations with the final Ethereum prices

Publisher: AIS Electronic Library (AISeL)
Year: 2019
OAI identifier: oai:aisel.aisnet.org:amcis2019-1378
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