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Algorithmic Short Selling with Python

Algorithmic Short Selling with Python

By : Laurent Bernut
4.7 (29)
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Algorithmic Short Selling with Python

Algorithmic Short Selling with Python

4.7 (29)
By: Laurent Bernut

Overview of this book

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.
Table of Contents (17 chapters)
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14
Other Books You May Enjoy
15
Index

The Long/Short Toolbox

Long-only portfolios are by definition correlated to the market. Introducing a short component enables managers to engineer the type of performance they want to deliver. We will make long/short portfolio management accessible to all dedicated market participants in this chapter.

Creating a long/short portfolio requires the consolidation of two relative portfolios: a long and a short book. The transition from a long-only or absolute long/short into a relative strength-long/short portfolio can be quite disconcerting at first. There are lots of moving parts. An effective way to manage this transition is to begin with the objectives in mind: liquidity, correlation, volatility, and performance. Then, concentrate on a handful of variables that have the highest impact on these objectives: gross and net exposure, net beta, and concentration, which make up your investment toolbox when constructing your strategy.

The following table indicates which of our objectives...

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Algorithmic Short Selling with Python
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