Complete set of 7 books to start algorithmic trading with Python:
Trading Evolved by Andreas Clenow
Professional backtesting environment using Python, and provides strategies for trading both futures and equities.
• Professional backtesting with Python
• Source code and strategy explanation
• Focus on futures and equities trading
Algorithmic Trading with Interactive Brokers by Matthew Scarpino
Introduces readers to algorithmic trading through Interactive Brokers' Trader Workstation (TWS) programming interface.
• Guide to using IB TWS API
• Focuses on Python and C++
• No prior experience needed
Learn Algorithmic Trading by Sebastien Donadio and Sourav Ghosh
Covers the trading system lifecycle, from idea generation to performance evaluation.
• Covers the trading system lifecycle
• Systematic approach to algo trading
• Uses Python and data analysis methods
Algorithmic Trading with Python by Chris Conlan
Modern quant trading methods in Python, with focus on pandas, numpy, and scikit-learn.
• Guides to build trading simulator
• Focuses on pandas, numpy, scikit-learn
• Teaches strategy optimization and ML pipeline1
Machine Learning for Algorithmic Trading by Stefan Jansen
Shows how machine learning can add value to algorithmic trading strategies in a practical way.
• Covers a broad range of ML
• Build, backtest, and evaluate strategies
• Demonstrates practical application of ML
Python for Algorithmic Trading Yves Hilpisch
Demystifies Python's role in algorithmic trading, enabling individual traders.
• Set up Python for trading
• Retrieve financial data effectively
• Master vectorized backtesting
Hands-On Financial Trading with Python by Jiri Pik and Sourav Ghosh
Guide to building and backtesting algorithmic trading strategies in Python.
• Understand quantitative analysis
• Access financial data in Python
• Implement effective data visualization12.
Learn from the best in the business:
• Andreas Clenow
• Matthew Scarpino
• Sebastien Donadio
• Sourav Ghosh
• Stefan Jansen
• Yves Hilpisch
• Chris Conlan
• Jiri Pik