2019 · 28 citations · 6 references
ComputingComputer ScienceData ScienceData MiningMachine LearningPredictive AnalyticsAlgorithmic TradingAlgorithmic Trading AnalyticsDecision TreesTime Series ClassificationTime Series ForecastingTime Series PredictionAnomaly Detection In TradingCryptocurrency HistoryFeature Engineering For Financial DataFinancial Time Series ForecastingMachine Learning Factor ModelsMachine Learning-based Price ForecastingPredictive Price ModelingRandom Forest Classification
In this study, we use random forest to predict several cryptocurrencies' prices by using part of factors in Alpha101 [1] to represent features from the history of cryptocurrencies' market data on Binance and Bitfinex. The result shows our strategy with some factors from Alpha101 is effective in cryptocurrency trading.
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Cryptocurrency price drivers: Wavelet coherence analysis revisited
Ross C. Phillips, Denise Gorse · PLoS ONE · 2018 · 137 citations · Full text
Predictive Analysis of Cryptocurrency Price Using Deep Learning
Yecheng Yao, Jungho Yi, Yu‐Wen Lin et al. · International Journal of Engineering & Technology · 2018 · 30 citations · Full text