Work2019

Using machine learning for cryptocurrency trading

31 citations0/0 files storedIEEE International Conference on Industrial Cyber-Physical Systems (ICPS)

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Blockchain Technology Applications and Security

Abstract

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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References

2018Cryptocurrency price drivers: Wavelet coherence analysis revisited 2017Predicting cryptocurrency price bubbles using social media data and epidemic modelling 2016101 Formulaic Alphas 2018Predictive Analysis of Cryptocurrency Price Using Deep Learning

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2022An automated cryptocurrency trading system based on the detection of unusual price movements with a Time-Series Clustering-Based approach

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