Published May 12, 2025
| Version v1.1
Software
Open
DonMask/Quantum-Reinforcement-Learning-for-High-Frequency-Trading-QRL-HFT-: Q-TradeRL
Authors/Creators
Description
This project explores the application of quantum reinforcement learning (QRL) techniques to high-frequency trading (HFT) strategies. The theoretical foundation is backed by a detailed LaTeX report covering quantum noise, fidelity decay, and the feasibility of using quantum circuits in trading environments.
Key aspects:
Benchmarking on IBMQ backends Fidelity analysis under depolarizing noise Modular and reproducible structure Academic and research-ready format
Files
DonMask/Quantum-Reinforcement-Learning-for-High-Frequency-Trading-QRL-HFT--v1.1.zip
Files
(138.2 kB)
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md5:33c65d8d38d366890a1f59c02c6f03db
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Additional details
Related works
- Is supplement to
- Software: https://github.com/DonMask/Quantum-Reinforcement-Learning-for-High-Frequency-Trading-QRL-HFT-/tree/v1.1 (URL)