In this project, we use XGBoost, KMeans, Hidden Markov Models, and a SAC Policy reinforcement learning agent to trade using 1 minute bid-only OHLC candle data on the EURUSD Forex pair. This only serves as a proof of concept as trading costs, market order book structure, and other complicating factors were not considered due to data limitations.
python finance neural-network random-forest fintech xgboost financial-data financial-analysis kmeans-clustering financial-markets hmm-model financial-modeling stable-baselines3 finacial-ml
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Updated
Feb 18, 2026 - Jupyter Notebook