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hmm-model

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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.

  • Updated Feb 18, 2026
  • Jupyter Notebook
Natural-Language-Processing-in-Python

A modular pipeline for constructing a long-only S&P 500 portfolio using fundamental and technical analysis, machine-learning forecasts and mean–variance optimisation. It supports local data sources or Yahoo Finance downloads, backtesting, risk management overlays, and produces performance metrics and visualisations out of the box.

  • Updated Jan 2, 2026
  • Python

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