Anticipating cryptocurrency prices using machine learning

TL;DR

This paper demonstrates that machine learning algorithms can effectively predict short-term cryptocurrency price movements, exploiting market inefficiencies to generate abnormal profits using simple trading strategies.

Contribution

It introduces a machine learning-based approach to predict cryptocurrency prices and shows these methods outperform standard benchmarks in short-term trading.

Findings

Machine learning algorithms outperform benchmarks in crypto trading

Simple algorithms can anticipate short-term market movements

Cryptocurrency market inefficiencies can be exploited for profit

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.