Work

Anticipating Cryptocurrency Prices Using Machine Learning

Year: 2018

Type: article

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.

Source: Complexity

DOI: 10.1155/2018/8983590

Authors: Laura Alessandretti, Abeer ElBahrawy, Luca Maria Aiello, Andrea Baronchelli

Institutions: Technical University of Denmark, City, University of London, Nokia (United Kingdom), University College London

Language: English

Topic: Stock Market Forecasting Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,760

OpenAlex ID: W2803148772