We can use reinforcement learning to build an automated trading bot in a few lines of Python code! In this video, i'll demonstrate how a popular reinforcement learning technique called "Q learning" allows an agent to approximate prices for stocks in a portfolio. The literature of reinforcement learning is incredibly rich. There are so many concepts, like TD-Learning and Actor-Critic for example, that have real-world potential. I hope this video gives you insight into how this incredibly powerful yet simple algorithm works, enjoy!
Code for this video:
https://github.com/llSourcell/Q-Learning-for-Trading
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Github Syllabus:
https://github.com/llSourcell/Move_37_Syllabus
More learning resources:
http://www.wildml.com/2018/02/introduction-to-learning-to-trade-with-reinforcement-learning/
http://cs229.stanford.edu/proj2009/LvDuZhai.pdf
https://medium.com/@gaurav1086/machine-learning-for-algorithmic-trading-f79201c8bac6
https://github.com/edwardhdlu/q-trader
http://www1.mate.polimi.it/~forma/Didattica/ProgettiPacs/BrambillaNecchi15-16/PACS_Report_Pierpaolo_Necchi.pdf
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