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Anticipating Cryptocurrency Prices Using Machine Learning

Laura Alessandretti, Abeer ElBahrawy, Luca Maria Aiello and Andrea Baronchelli

Complexity, 2018, vol. 2018, 1-16

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 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.

Date: 2018
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Citations: View citations in EconPapers (23)

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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8983590

DOI: 10.1155/2018/8983590

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