Time Series Analysis of Cryptocurrency Prices Using Long Short-Term Memory
Time Series Analysis of Cryptocurrency Prices Using Long Short-Term Memory
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DOI：
10.3390/a15070230
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发表时间：
2022-07-01
期刊：
影响因子：
2.3
通讯作者：
Bautista, Yohn Jairo Parra
中科院分区：
文献类型：
--
作者：
Fleischer, Jacques Phillipe;von Laszewski, Gregor;Bautista, Yohn Jairo Parra
数字化正在改变我们的世界，创造创新的金融渠道和新兴技术，如加密货币，这是区块链技术的应用。然而，加密货币价格波动是这项技术的主要权衡之一。在本文中，我们将探索使用深度学习的时间序列分析来研究波动性并理解这种行为。我们应用长短期记忆模型来学习加密货币收盘价的模式，并预测未来的价格。所提出的模型从接近的值中学习。该模型的性能进行评估，使用均方根误差，并通过比较它的ARIMA模型。
Digitization is changing our world, creating innovative finance channels and emerging technology such as cryptocurrencies, which are applications of blockchain technology. However, cryptocurrency price volatility is one of this technology's main trade-offs. In this paper, we explore a time series analysis using deep learning to study the volatility and to understand this behavior. We apply a long short-term memory model to learn the patterns within cryptocurrency close prices and to predict future prices. The proposed model learns from the close values. The performance of this model is evaluated using the root-mean-squared error and by comparing it to an ARIMA model.