Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Algorithmic Short Selling with Python
  • Table Of Contents Toc
Algorithmic Short Selling with Python

Algorithmic Short Selling with Python - Second Edition

By : Laurent Bernut
close
close
Algorithmic Short Selling with Python

Algorithmic Short Selling with Python

By: Laurent Bernut

Overview of this book

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.
Table of Contents (16 chapters)
close
close
Lock Free Chapter
1
Part 1: The Short Selling Game
5
Part 2: The Outer Game: The Trading Edge
10
Part 3: The Long/Short Game: Portfolio Construction
15
Index

3

Long/Short Methodologies: Absolute and Relative

In this chapter, we will be comparing methodologies, with a particular focus on absolute versus relative series. We will move from a scarcity to an abundance of ideas. We will find an easy to shop for potential Short and Long candidates via sector rotation. Absolute series are the Open High Low Close (OHLC) prices you can see on any website or platform. They often come either adjusted for dividends, stock splits, and other corporate actions. Relative series are the above absolute series divided by the closing price of the benchmark, adjusted for currency.

We will demonstrate the weakness of the absolute method, and strength of the relative weakness method, which will define our methodology for the rest of the book. Our objective is to broaden the investment universe from the rare stocks tanking in absolute to half the constituents that underperform the index at any point in time.

We will cover the following topics on the...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Algorithmic Short Selling with Python
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon