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Key benefits

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

Description

If you are in the long/short business, learning how to sell short is not a choice. Short selling is the key to raising assets under management. This book will help you demystify and hone the short selling craft, providing Python source code to construct a robust long/short portfolio. It discusses fundamental and advanced trading concepts from the perspective of a veteran short seller. This book will take you on a journey from an idea (“buy bullish stocks, sell bearish ones”) to becoming part of the elite club of long/short hedge fund algorithmic traders. You’ll explore key concepts such as trading psychology, trading edge, regime definition, signal processing, position sizing, risk management, and asset allocation, one obstacle at a time. Along the way, you’ll will discover simple methods to consistently generate investment ideas, and consider variables that impact returns, volatility, and overall attractiveness of returns. By the end of this book, you’ll not only become familiar with some of the most sophisticated concepts in capital markets, but also have Python source code to construct a long/short product that investors are bound to find attractive.

Who is this book 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.

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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

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Machine Learning for Algorithmic Trading

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Total zł 645.97

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Amazon verified reviews

Guy R. Porter Sep 24, 2022

If you're trading for your own account or managing portfolios for other investors, the insights in this book are priceless. As a short seller, Bernut's methods shine in market crashes especially. But long only managers have much to learn from what's in this book.As Ken Grant noted in "Trading Risk," every manager needs to make sure at least some part of the portfolio does better when the benchmark sinks. And that's a big part of what is addressed here.About two thirds of the book is NOT about short-selling, but about making any trading system better. Bernut provides a set of rational, step by step methods for developing, deploying, monitoring and improving your best ideas for trading systems.Here are a few highlights:If you ask 10 traders what their edge is, 8 of them will tell you a story instead. Winners and professionals quantify that edge and their strategy (pp 109 - 133)I liked the refreshingly frank talk about what your stops should be and how they should be enforced. Operational Risk (the chance of a manager making a mistake) is the largest risk among individuals and you'll find solid measures here to shore up weaknesses to improve your results quantifiably (pp134-169).If you're still using the "2% risk per trade heuristic," you really need to understand your peril better. Especially true in times of market chaos, position sizing is the link between your financial and your emotional capital. (pp171-202)ABOUT THE PROGRAMMING PART: I have only a passing knowledge of Python, therefore much of the real gold is hidden from me so far. The narrative itself is enough to provide a good guide. However, if you have been moved, as I have, to study and learn to program in order to automate what can be automated, there is even more value here with code supplied through GitHub and color graphics available through the publishers website.

Amazon Verified review

Daniel Feb 04, 2023

Insightful and enjoyable read. I am Groot.

Ivan Vasilev Oct 25, 2021

The book was clearly written with passion and it shows the author's in-depth knowledge and hands-on experience in the financial field.

Michal Malík Aug 21, 2022

This book is a book I will be periodically returning to in my trading journey. Reading it I realized that there is more to the market than I had ever thought. My brain also found out new ways to approach the market and a guideline on how to create a trading system and how to grade it. The source code is a great addition. The book gives a general outline of what the code does and the code show details and implementation. They complement each other and make the point clear. Finally, Laurent understands that even with a trading system, we are humans, not machines and gives us tips to better sleep at night.

Amazon Customer May 16, 2022

I’ve known about Laurent Bernut for a couple years from his Quara posts. I purchased his book day one and have been absorbing the content ever since. I am a young software engineer with no professional trading knowledge, only self taught. I have made significant progress building my own trading system using the ideas in this book. The main value of this book is it teaches the building blocks of creating a successful strategy, while providing a very generous starting point with the code provided.

Algorithmic Short Selling with Python: Refine your algorithmic trading edge, consistently generate investment ideas, and build a robust long/short product

What do you get with eBook?