Master algorithmic short selling with Python by learning practical techniques, coding trading signals, and applying robust risk management to generate alpha in any market condition.
Key Features
- Build and test algorithmic short-selling strategies in Python
- Apply advanced trade execution, position sizing, and risk controls
- Harness idea generation, regime detection, position sizing, pairs trading, portfolio management, and asset allocation
Book Description
Algorithmic Short Selling with Python, Second Edition is a practical guide to building, testing, and managing systematic short-selling strategies in today's markets. Structured around the core challenges every short seller faces, the book provides a framework for continuously generating long/short ideas, identifying bullish/bearish market regimes, detecting sector rotation ahead of consensus, constructing robust long/short portfolios, and managing the unique risks of the short side. Through real-world examples and working Python code based on S&P 500 data, readers learn how to develop quantitative strategies that address position sizing, crowded trades, portfolio exposures, and capital allocation across changing market conditions. The book also explores advanced topics such as relative strength analysis, fractals, convexity, long/short portfolio management, asset allocation, and the use of AI-powered trading journals to uncover the behavioral patterns that influence trading decisions. Every concept is supported by implementation, bridging the gap between theory and execution. Expanding on the first edition, this updated version transforms ideas into fully coded solutions, providing readers with the tools to design, evaluate, and deploy systematic short-selling strategies with confidence, discipline, and consistency.
What you will learn
- Generate long and short ideas across all types of markets
- Systematically classify securities as bullish or bearish
- Detect sector rotation ahead of consensus
- Apply risk-adjusted position sizing tailored to short selling
- Avoid crowded trades, go long short squeezes, and navigate high dividend yield value traps
- Manage a long/short portfolio with four exposures: gross, net, Beta, and concentration
- Combine uncorrelated strategies to generate a smoother equity curve
- Use an AI-powered trading journal to elicit subconscious beliefs that drive your trading decisions
Who this book is for
This book is for quantitative traders, portfolio managers, algorithmic trading developers, and advanced retail traders who want to master the short side using Python. A working knowledge of Python and basic trading concepts is assumed. Readers will gain not just coding skills, but also the strategic and risk management frameworks needed to build profitable short strategies.
