Reinforcement-Learning-for-Algorithmic-Trading-A-Q-Learning-Approach-to-Strategy-Optimization

This project analyzes two algorithmic trading strategies: the first one is a simple rule-based strategy, the second one leverages a Reinforcement Learning (RL) approach using Q-Learning

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Forks: 0
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License: None
Language: R
Size: 332 KB
Dependencies parsed at: Pending

Created at: about 2 months ago
Updated at: about 1 month ago
Pushed at: about 1 month ago
Last synced at: about 1 month ago

Topics: bollinger-bands, macd, q-learning, reinforcement-learning, reinforcement-learning-algorithms, trading-strategies

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GitHub / DavideDevetak24 / Reinforcement-Learning-for-Algorithmic-Trading-A-Q-Learning-Approach-to-Strategy-Optimization