Forecasting Cryptocurrency Prices Using LSTM, GRU, and Bi-Directional LSTM: A Deep Learning Approach
Sefako Makgatho Health Sciences University · University of Pretoria
Abstract
Highly accurate cryptocurrency price predictions are of paramount interest to investors and researchers. However, owing to the nonlinearity of the cryptocurrency market, it is difficult to assess the distinct nature of time-series data, resulting in challenges in generating appropriate price predictions. Numerous studies have been conducted on cryptocurrency price prediction using different Deep Learning (DL) based algorithms. This study proposes three types of Recurrent Neural Networks (RNNs): namely, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bi-Directional LSTM (Bi-LSTM) for exchange rate predictions of three major cryptocurrencies in the world, as measured by their market…
Citation impact
- FWCI
- 82.23
- Percentile
- 100%
- References
- 35
Authors
3Topics & keywords
- Cryptocurrency
- Mean absolute percentage error
- Market capitalization
- Mean squared error
- Computer science
- Artificial intelligence
- Deep learning
- Econometrics