Paperback. 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 FeaturesBuild and test algorithmic short-selling strategies in PythonApply advanced trade execution, position sizing, and risk controlsHarness idea generation, regime detection, position sizing, pairs trading, portfolio management, and asset allocationBook DescriptionAlgorithmic 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 learnGenerate long and short ideas across all types of marketsSystematically classify securities as bullish or bearishDetect sector rotation ahead of consensusApply risk-adjusted position sizing tailored to short sellingAvoid crowded trades, go long short squeezes, and navigate high dividend yield value trapsManage a long/short portfolio with four exposures: gross, net, Beta, and concentrationCombine uncorrelated strategies to generate a smoother equity curveUse an AI-powered trading journal to elicit subconscious beliefs that drive your trading decisionsWho this book is forThis 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. This book equips quantitative traders and portfolio managers with a complete Python framework for algorithmic short selling. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Bibliographic Details

Title: Algorithmic Short Selling with Python (Paperback)
Publisher: Packt Publishing Limited, Birmingham
Publication Date: 2026
Language: English
ISBN 10: 1806025930
ISBN 13: 9781806025930
Binding: Paperback
Edition: 2nd Edition
Condition: new

About this title

Synopsis

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.

The Stock Market Game
10 Classic Myths About Short Selling
Long/Short Methodologies: Absolute and Relative
Regime Definition
The Trading Edge is a Number, and Here is the Formula
Position Sizing: Money is Made in the Money Management Module
Refining the Investment Universe
The Long/Short Toolbox
Asset Allocation
The Trading Journal

About the Author

Laurent Bernut is a hedge fund veteran and short-selling specialist with over 20 years of experience across global financial markets. He has worked for prestigious institutions including Fidelity Japan and two major long/short hedge funds, where he honed his expertise in quantitative trading and portfolio management systems. Laurent has built quantitative trading tools and portfolio management systems used by professionals worldwide. Passionate about education and strategy development, he brings deep insight into market dynamics, risk, and portfolio construction.

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