Anticipating Cryptocurrency Prices Using Machine Learning. (4th November 2018)

• Record Type: Journal Article
• Authors: Alessandretti, Laura; ElBahrawy, Abeer; Aiello, Luca Maria; Baronchelli, Andrea
• Other Names: Zanin Massimiliano Academic Editor.
• Is Part Of: Complexity. Volume 2018(2018)
• Publication Date: 2018-11-04
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2018/8983590
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Machine learning and AI-assisted trading have attracted growing interest for the past few years. Here, we use this approach to test the hypothesis that the inefficiency of the cryptocurrency market can be exploited to generate abnormal profits. We analyse daily data for 1, 681 cryptocurrencies for the period between Nov. 2015 and Apr. 2018. We show that simple trading strategies assisted by state-of-the-art machine learning algorithms outperform standard benchmarks. Our results show that nontrivial, but ultimately simple, algorithmic mechanisms can help anticipate the short-term evolution of the cryptocurrency market.