Recommended Books for Algorithmic Trading

Categories of Books

The speaker organized the books into seven categories:

Systematic Trading by Robert Carver
- Great starting point
- Emphasizes simple trading rules & realistic expectations
- Modular framework for trading systems
Trading Systems and Methods by Perry Kaufman
- Encyclopedia of trading systems and indicators
- Useful as a reference
Advances in Financial Machine Learning
- Focus on overfitting in trading system development
- Topics like sampling, labeling, feature importance, cross-validation
- Provides Python implementations

The Leverage Space Trading Model by Ralph Vince
- Storybook format, engaging
- Managing risk in various trading scenarios
- Concepts of leverage space
The Mathematics of Money Management by Ralph Vince
- Textbook format
- Topics like trade dependence, arc sign loss, parametric distributions

Books by John Ehlers
- Digital signal processing techniques
- Methods for detecting cycles, smoothing filters, & novel indicators
- Easy language code, convert to other languages
Statistically Sound Indicators for Financial Market Prediction by Timothy Masters
- Indicators like MACD, RSI, Stochastic, & unique ones
- Topics on indicator stationarity, normalization, information content

The Universal Tactics of Successful Trend Trading by Brent Penfold
- Classic trend following strategies
- History of trend following
Stocks on the Move by Andreas Clenow
- Relative momentum strategy and examples
Cybernetic Trading Strategies by Murray Ruggiero
- Seasonality, intermarket analysis, genetic algorithms, exit design
- Introduction to meta labeling

Testing and Tuning Market Trading Systems by Timothy Masters
- Comprehensive survey of walk forward methods
- Discusses avoiding data overlap
- Differential Evolution optimization algorithm
Permutation and Randomization Tests for Trading System Development by Timothy Masters
- Monte Carlo permutation tests
- Data mining-based trading systems

Numerical Recipes: The Art of Scientific Computing
- Algorithms for optimization, modeling, spectral analysis
Assessing and Improving Prediction and Classification by Timothy Masters
- Methods for improving models, combining weaker models
Data-Driven Science and Engineering by Steve Brunton and Nathan Kutz
- Techniques like Dynamic Mode Decomposition

Technical Analysis for Algorithmic Pattern Recognition
- Automation techniques and unbiased technical analysis
Detecting Regime Change and Computational Finance
- Directional change algorithm & hidden Markov model for market regimes
Trading on Sentiment by Richard Peterson
- Building sentiment indicators, theories on market sentiment impact