Book Image

Algorithmic Short Selling with Python

By : Laurent Bernut
Book Image

Algorithmic Short Selling with Python

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)
14
Other Books You May Enjoy
15
Index

Summary

We have examined a few regime methodologies that will help you pick up on signals that a market is going up or down. Regime breakouts and moving average crossovers are staples in the arsenal of trend-following traders. Duration is as much a function of style as what the market happens to reward. Then, we introduced the floor/ceiling methodology. This regime definition method works on absolute and relative series. It is symmetrical and above all more stable than any other methodology. It therefore supersedes everything else.

However, regime definition methodologies are not mutually exclusive. For example, the floor/ceiling method could be used to determine the direction of trades, long or short. Then, regime breakout could be used to enter after consolidation or sideways markets. Finally, the moving average crossover could be used to exit positions.

Having a signal is one thing. Turning it into a profitable strategy with a robust statistical edge is another. There is...