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Algorithmic Short Selling with Python

You're reading from   Algorithmic Short Selling with Python Refine your algorithmic trading edge, consistently generate investment ideas, and build a robust long/short product

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781801815192
Length 376 pages
Edition 1st Edition
Languages
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Author (1):
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Laurent Bernut Laurent Bernut
Author Profile Icon Laurent Bernut
Laurent Bernut
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Table of Contents (17) Chapters Close

Preface The Stock Market Game 10 Classic Myths About Short Selling FREE CHAPTER 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 Other Books You May Enjoy
Index
Appendix: Stock Screening

Myth #8: Short selling collapses share prices

Short sellers simply do not have the firepower to torpedo share prices. Short sellers need to borrow shares in order to sell short. This comes from shareholders who lend a fraction of their holdings to stock loan desks. Borrow availability usually averages less than 10% of the free float, in other words, the portion of shares available to public investors. This means that short sellers represent a fraction of the overall sell volume.

The BB guns of short sellers may have a punctual market impact, but the real damage is inflicted by the heavy artillery of institutional investors selling. This leads us to an interesting point about short selling. Making money on the short side is not about spotting stocks that could potentially go down. It is about riding the tail of institutional investors liquidating their positions.

You have been reading a chapter from
Algorithmic Short Selling with Python
Published in: Sep 2021
Publisher: Packt
ISBN-13: 9781801815192
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