2021-03-15 09:11:29
ML for Trading - 2nd Edition: This book aims to show how ML can add value to algorithmic trading strategies in a practical yet comprehensive way. It covers a broad range of ML techniques from linear regression to deep reinforcement learning and demonstrates how to build, backtest, and evaluate a trading strategy driven by model predictions.
This
repo: https://github.com/stefan-jansen/machine-learning-for-trading contains over 150 notebooks that put the concepts, algorithms, and use cases discussed in the book into action. They provide numerous examples that show:
- how to work with and extract signals from market, fundamental and alternative text and image data,
- how to train and tune models that predict returns for different asset classes and investment horizons, including how to replicate recently published research, and
- how to design, backtest, and evaluate trading strategies.
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