Predicting Price Direction of Cryptocurrency Using Artificial Neural Networks
Abstract
The machine learning method has been used in stock price prediction for a long time, and the price of cryptocurrencies such as bitcoin has attracted more and more attention in recent years. This paper aims to improve the method applicable to the stock market and try to use it in cryptocurrency price prediction. A simple three-layered feedforward artificial neural networks (ANN) model was applied in this paper to predict the daily directions of cryptocurrency prices. The historical trading data of Bitcoin, Ethereum, and Cardano were used in the experiments. Nine selected technical indicators were preprocessed into discrete trend data, and they were input into the model together with three additional indicators for training. This study has preliminarily obtained an effective result with price prediction accuracy of the three cryptocurrencies between 61% and 65%.
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