Bitcoin Vision: Using Machine Learning and Data Mining to Predict the Short-Term and Long-Term Price of Bitcoin
Bitcoin Vision: Using Machine Learning and Data Mining to Predict the Short-Term and Long-Term Price of Bitcoin
复制标题
比特币愿景：利用机器学习和数据挖掘来预测比特币的短期和长期价格
DOI：
10.14704/web/v18si05/web18259
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
M. Joseph
中科院分区：
文献类型：
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作者：
E. Millikan;Preethi Subramanian;M. Joseph
加密货币是一种非物理货币，仅以0和1的形式存在于计算机世界中。目前市场上最受欢迎的加密货币之一是比特币，它最初是为了解决在线购买时使用传统货币的固有问题而发明的。然而，出乎意料的是，比特币很快就发现自己是最有利可图的投资机会之一，其年增长率是股票、债券或房地产等传统投资产品无法比拟的。然而，与成为众多研究论文主题的股市不同，加密货币市场并未受到同样的对待，因此该行业仍存在巨大的机会。因此，Bitcoin Vision希望利用这个机会，并提出使用机器学习和深度学习架构来预测比特币的短期价格走势（上涨或下跌），并预测比特币的长期价格。能够预测市场的未来被证明在股票市场上是有用的，因此本文决定在加密货币市场上也复制这个机会。在这篇文献综述论文中，我们提出了将最先进的深度学习模型（如长短期记忆（LSTM））与传统上成功的机器学习模型（如随机森林和ARIMA）进行比较，以找出哪种模型提供最佳结果。
Cryptocurrencies are non-physical currency that solely exist as represented by 0s and 1s within the world of computers. One of the most popular cryptocurrencies in the market right now being Bitcoin, was first invented to solve the inherent problem with using traditional currency when purchasing online. However, unexpectedly Bitcoin soon found itself to be one of the most profitable investment opportunities to be hedged on with its yearly growth unrivaled by any traditional investment product such as stocks, bonds, or real-estate. However, unlike the stock market which has been the subject of multitude of research papers, the cryptocurrency market has not been treated the same way and as such there is still a huge opportunity open in this industry. Thus, Bitcoin Vision wants to utilize this opportunity and propose the use of machine learning and deep learning architecture to predict the price movement trend of bitcoin (up or down) for the short-term prediction and predict the price of bitcoin for the long-term prediction. Being able to predict the future of the market prove to be useful in the stock market and as such this paper decide to replicate that opportunity to be presented in the cryptocurrency market as well. In this literature review paper, we have proposed the comparison of state-of-the-art deep learning model such as Long Short-Term Memory (LSTM) with traditionally successful machine learning model such as Random Forest and ARIMA to find out which model provide the best result.