Machine Learning Applied to Stock & Crypto Trading – Python

Use Unsupervised, Supervised and Reinforcement Learning techniques to gain an edge in trading Stocks, Crypto, Forex...

Created by: Shaun McDonogh
Lead Analyst and Full Stack (Python and React) Developer

What Will I Learn?

• Understand hidden states and regimes for any market or asset using Hidden Markov Models
• Discover optimum assets for pairs trading in ETF's, Stocks, Forex or Crypto using K-Means Clustering
• Condense information from a vast array of indicators with PCA
• Make objective future predictions on financial data with XGBOOST
• Train an AI Reinforcement Learning agent to trade stocks with PPO
• Test for market efficiency on any given asset
• Become familiar with Python Libraries including Pandas, PyTorch (for deep learning) and sklearn

Requirements

• You should have some basic experience with Python
• You should be aware of trading related concepts like Pairs Trading
• You should have awareness of assets like ETF's, the VIX, Stocks and Crypto

Target audience

• Retail traders who are looking to gain an objective edge in the financial markets
• Enthusiasts who are looking for a practical and fun application of Machine Learning