Deep Learning Bitcoin Price Prediction
Bryan DeHart
This podcast explores the use of deep learning to predict Bitcoin price direction. Several deep learning models, including CNN-LSTM, LSTNet, and TCN, are compared to an ARIMA model as a benchmark. Feature selection methods are employed to optimize model performance. The results show that the combination of Boruta feature selection with the CNN-LSTM model outperforms others, achieving an accuracy of 82.44% and generating extraordinary annual returns in simulated investment strategies. The study highlights the potential of predictive models in Bitcoin trading, while acknowledging limitations and suggesting areas for future research.
Duration - 15m.
Author - Bryan DeHart.
Narrator - Lucy Wilson.
Published Date - Friday, 12 January 2024.
Copyright - © 2024 Loudly ©.
Location:
United States
Description:
This podcast explores the use of deep learning to predict Bitcoin price direction. Several deep learning models, including CNN-LSTM, LSTNet, and TCN, are compared to an ARIMA model as a benchmark. Feature selection methods are employed to optimize model performance. The results show that the combination of Boruta feature selection with the CNN-LSTM model outperforms others, achieving an accuracy of 82.44% and generating extraordinary annual returns in simulated investment strategies. The study highlights the potential of predictive models in Bitcoin trading, while acknowledging limitations and suggesting areas for future research. Duration - 15m. Author - Bryan DeHart. Narrator - Lucy Wilson. Published Date - Friday, 12 January 2024. Copyright - © 2024 Loudly ©.
Language:
English
Deep Learning Bitcoin Price Prediction
Duration:00:15:50