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A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms

Department of Natural, Engineering and Technology Sciences, Arab American University, Ramallah P600, Palestine
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Academic Editor: Amir Mosavi
AI 2021, 2(4), 477-496; https://doi.org/10.3390/ai2040030
Received: 8 September 2021 / Revised: 4 October 2021 / Accepted: 5 October 2021 / Published: 13 October 2021
Cryptocurrency is a new sort of asset that has emerged as a result of the advancement of financial technology and it has created a big opportunity for researches. Cryptocurrency price forecasting is difficult due to price volatility and dynamism. Around the world, there are hundreds of cryptocurrencies that are used. This paper proposes three types of recurrent neural network (RNN) algorithms used to predict the prices of three types of cryptocurrencies, namely Bitcoin (BTC), Litecoin (LTC), and Ethereum (ETH). The models show excellent predictions depending on the mean absolute percentage error (MAPE). Results obtained from these models show that the gated recurrent unit (GRU) performed better in prediction for all types of cryptocurrency than the long short-term memory (LSTM) and bidirectional LSTM (bi-LSTM) models. Therefore, it can be considered the best algorithm. GRU presents the most accurate prediction for LTC with MAPE percentages of 0.2454%, 0.8267%, and 0.2116% for BTC, ETH, and LTC, respectively. The bi-LSTM algorithm presents the lowest prediction result compared with the other two algorithms as the MAPE percentages are: 5.990%, 6.85%, and 2.332% for BTC, ETH, and LTC, respectively. Overall, the prediction models in this paper represent accurate results close to the actual prices of cryptocurrencies. The importance of having these models is that they can have significant economic ramifications by helping investors and traders to pinpoint cryptocurrency sales and purchasing. As a plan for future work, a recommendation is made to investigate other factors that might affect the prices of cryptocurrency market such as social media, tweets, and trading volume. View Full-Text
Keywords: cryptography; blockchain; cryptocurrency; artificial intelligence (AI); machine learning cryptography; blockchain; cryptocurrency; artificial intelligence (AI); machine learning
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MDPI and ACS Style

Hamayel, M.J.; Owda, A.Y. A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms. AI 2021, 2, 477-496. https://doi.org/10.3390/ai2040030

AMA Style

Hamayel MJ, Owda AY. A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms. AI. 2021; 2(4):477-496. https://doi.org/10.3390/ai2040030

Chicago/Turabian Style

Hamayel, Mohammad J., and Amani Y. Owda 2021. "A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms" AI 2, no. 4: 477-496. https://doi.org/10.3390/ai2040030

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