基于LSTM网络和强化学习的比特币价格预测和自动交易

Ioannis Ntourmas, Dionisios N. Sotiropoulos
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引用次数: 0

摘要

比特币(BTC)是最受欢迎的加密货币之一,现在是股票市场上的一种投资。价格预测是一个真正的挑战,因为它取决于太多的因素,对比特币的投资风险太大,因为价格有太多的反转。然而,BTC是许多人开始探索股票市场的机会。在过去的几年里,BTC的预测占据了科学界,并提出了许多方法。在这项研究中,我们试图用长短期记忆网络预测每分钟比特币的价格,然后将这些预测传递给一个循环强化学习(RRL)模型,用美元(USD)交易比特币。在论文的最后,我们给出了模型所带来的收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bitcoin Price Prediction and Automated Trading via LSTM Networks and Reinforcement Learning
The Bitcoin (BTC) is one of the most popular cryptocurrencies and now is one type of investment on the stock market. The price prediction is a real challenge as it depends by too many factors, an investment to BTC characterized too risky because the price has too many upside-downs. However BTC was the occasion for many people to start explore the stock market. In the last few years, the prediction of BTC has occupied the scientific community and many approaches have been made. In this research we try to predict the price of BTC per minute with long short-term memory networks, and then pass these predictions to a recurrent reinforcement learning (RRL) model to trade the BTC with United States dollars (USD). In the end of the paper we present the profits that the models made.
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