A profitable trading algorithm for cryptocurrencies using a Neural Network model

【Author】 Parente, Mimmo; Rizzuti, Luca; Trerotola, Mario

【Source】EXPERT SYSTEMS WITH APPLICATIONS

【影响因子】8.665

【Abstract】Algorithmic trading enables the execution of orders using a set of rules determined by a computer program. Orders are submitted based on an asset's expected price in the future, an approach well suited for high-volatility markets, such as those trading in cryptocurrencies. The goal of this study is to find a reliable and profitable model to predict the future direction of a crypto asset's price based on publicly available historical data. We first develop a novel labeling scheme and map this problem into a Machine Learning classification problem. The model is then validated on three major cryptocurrencies through an extensive backtest over a bull, bear and flat market. Finally, the contribution of each feature to the classification output is analyzed.

【Keywords】Cryptocurrencies; Machine learning; Neural network; Price prediction; Algorithmic trading; Explainable AI; Backtesting; Shapley values

【发表时间】2024 15-Mar

【收录时间】2023-11-08

【文献类型】理论模型

【主题类别】

区块链应用-虚拟经济-虚拟货币