Enhanced Bitcoin Price Direction Forecasting With DQN

Enhanced Bitcoin Price Direction Forecasting With DQN

In the Bitcoin trading landscape, predicting price movements is paramount. Our study focuses on identifying the key factors influencing these price fluctuations. Utilizing the Pearson correlation method, we extract essential data points from a comprehensive set of 14 data features. We consider histo...

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Bibliographic Details
Main Authors: Azamjon Muminov, Otabek Sattarov, Daeyoung Na
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Bitcoin
reinforcement learning
deep Q-network
Pearson correlation
reward function
Online Access:https://ieeexplore.ieee.org/document/10440336/

Internet

https://ieeexplore.ieee.org/document/10440336/

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