Bridging Theory and Practice: ML Solutions for Today’s Challenges
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- ML Engineering and Optimization
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Algorithmic Short Selling with Python, Published by Packt
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.
- 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
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.
- The Stock Market Game
- 10 Classic Myths About Short-Selling
- Take a Walk on the Wild Short-Side
- Long/Short Methodologies: Absolute and Relative
- Regime Definition
- The Trading Edge is a Number, and Here is the Formula
- Improve Your Trading Edge
- Position Sizing: Money is Made in the Money Management Module
- Risk is a number
- Refining the Investment Universe
- The Long/Short Toolbox
- Signals and Execution
- Portfolio Management System
- Appendix: Stock Screening
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.
