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Algorithmic-Short-Selling-with-Python

Algorithmic Short Selling with Python, Published by Packt

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Key Features

Understand techniques such as trend following, mean reversion, position sizing, and risk management in a short-selling context. Implement Python source code to explore and develop your own investment strategy. Test your trading strategies to limit risk and increase profits.

What you will learn

  • Develop the mindset required to win the infinite, complex, random game called the stock market
  • Demystify short selling in order to generate alpa in bull, bear, and sideways markets
  • Generate ideas consistently on both sides of the portfolio
  • Implement Python source code to engineer a statistically robust trading edge
  • Develop superior risk management habits
  • Build a long/short product that investors will find appealing

Who This Book Is For

This is a book by a practitioner for practitioners. It is designed to benefit a wide range of people, including long/short market participants, quantitative participants, proprietary traders, commodity trading advisors, retail investors (pro retailers, students, and retail quants), and long-only investors.

At least 2 years of active trading experience, intermediate-level experience of the Python programming language, and basic mathematical literacy (basic statistics and algebra) are expected.

Table of Contents

  1. The Stock Market Game
  2. 10 Classic Myths About Short-Selling
  3. Take a Walk on the Wild Short-Side
  4. Long/Short Methodologies: Absolute and Relative
  5. Regime Definition
  6. The Trading Edge is a Number, and Here is the Formula
  7. Improve Your Trading Edge
  8. Position Sizing: Money is Made in the Money Management Module
  9. Risk is a number
  10. Refining the Investment Universe
  11. The Long/Short Toolbox
  12. Signals and Execution
  13. Portfolio Management System
  14. Appendix: Stock Screening

Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

https://packt.link/free-ebook/9781801815192

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