ucaiado/QLearning_Trading
Learning to trade under the reinforcement learning framework
This project helps financial traders develop an adaptive strategy for trading a single stock. By inputting historical stock data, it trains an agent through a reward/punishment system to learn and maximize profits. The output is a trading strategy that has learned from experience. This tool is for individual traders or quantitative analysts looking to automate and optimize their trading decisions.
517 stars. No commits in the last 6 months.
Use this if you want to explore reinforcement learning to create an automated trading strategy for a single stock and understand its performance through simulation.
Not ideal if you need a real-time trading system for multiple assets, a solution for high-frequency trading, or an out-of-the-box system without any technical setup.
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517
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181
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Jupyter Notebook
License
Apache-2.0
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Last pushed
Oct 15, 2016
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