ml4algotrading

Notes for Machine Learning for Algorithmic Trading 2ed 2020 (by Jansen Stefan)

Preface

ML gives an additional value in any industry, in trading and investing too. Novell approaches to quantitative investment. Trading scope across multiple asset is huge. ML can give insights with alternative data. You need statistics, computational skills, domain expertise to ask right questions and identify data in a way to right decisions. Book provide an integrated perspective on the application of ML to domain of investment and trading.

What to expect

• focus on ML4T: generate ideas, sourcing data, extract features, design trading strategy, backtest
• apply broad range of ML to trade various classes of assets, tools to interpret the results
• gain value from alternative data
• challenges for ML in the trading domain: lower signal content, shorter time series, etc. Hard to achieve robust results
• book is a guide to leveraging ML algos to form trading strategy. use it following workflow:
  • Sourcing, evaluating, and combining data for any investment objective
  • Designing and tuning ML models that extract predictive signals from the data
  • Developing and evaluating trading strategies based on the results
• after reading this book, you will be able to begin designing and evaluating your own ML-based strategies

What's new in the second edition