LiamConnell/deep-algotrading
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
This project helps quantitative traders and financial analysts explore how deep learning can be applied to algorithmic trading. It takes historical financial data, such as stock prices, and processes it through various deep learning models to predict future price movements or directly make trading decisions (long/neutral/short positions). The output is a demonstration of how different models perform in a trading context, providing insights into potential strategies.
245 stars. No commits in the last 6 months.
Use this if you are a quantitative trader or financial analyst interested in learning and experimenting with deep learning techniques for developing algorithmic trading strategies.
Not ideal if you are looking for ready-to-deploy, battle-tested trading algorithms, as many examples are for educational purposes and may not be viable strategies.
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245
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76
Language
Jupyter Notebook
License
MIT
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Last pushed
Jun 10, 2024
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