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

Net exposure

Net exposure is the percentage difference between long and short exposures. Net exposure is an approximate reflection of the directional view on the markets: bullish when positive, bearish when negative. Net exposure has a direct impact on:

  • Liquidity is one of the most overlooked and critical components. Long and short positions have opposite dynamics. To keep net exposure low, the short book needs to be constantly replenished. Meanwhile, the supply of borrow is finite. This leads to an increase in borrowing costs. Always keep an eye on borrow utilization. Do not let it go past around 66%.
  • Correlation: The lower the net exposure, the lower the correlation. Mutual funds have a correlation of 1, for instance, meaning they mirror the market gyrations. Markets go up, so do mutual funds, and vice versa on the way down.
  • Volatility: Net exposure has the largest impact on volatility. The lower the net, the lower the volatility. Targeting zero net exposure...