Complexity · 2018 · 229 citations · 50 references
ComputingComputer ScienceFinanceArtificial IntelligenceForecastingMachine LearningAlgorithmic TradingAlgorithmic Trading AnalyticsDeep LearningMarket AnomaliesTime Series ForecastingTime Series PredictionAnomaly Detection In TradingDeep Learning-based Price ForecastingMachine Learning Forecasting ModelsMachine Learning-based ForecastingMachine Learning-based Price ForecastingPredictive Price Modeling
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.
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