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Algorithmic Short Selling with Python

You're reading from  Algorithmic Short Selling with Python

Product type Book
Published in Sep 2021
Publisher Packt
ISBN-13 9781801815192
Pages 376 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Laurent Bernut Laurent Bernut
Profile icon Laurent Bernut
LinkedIn
Laurent Bernut has 2 decades of experience in alternative investment space. After the US CPA, he compiled financial statements in Japanese and English for a Tokyo Stock Exchange-listed corporation. After serving as an analyst in two Tokyo-based hedge funds, he joined Fidelity Investments Japan as a dedicated quantitative short-seller. Laurent has built numerous portfolio management systems and developed several quantitative models across various platforms. He currently writes and runs algorithmic strategies and is an undisputed authority on short selling on Quora, where he was nominated top writer for 2017, 2018, and 2019.
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Table of Contents (17) Chapters

Preface The Stock Market Game 10 Classic Myths About Short Selling 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

A trading edge is not a story

"If you can't measure it, you can't improve it."

– Peter Drucker

A trading edge is not a story. A trading edge is a number, and the formula is composed of a few functions:

  1. Arithmetic gain expectancy: In execution trader English, this is how often you win multiplied by how much you make on average minus how often you lose times how much you lose on average. This function is the classic arithmetic expectancy, present in every middle school introduction to statistics and absent in a Finance MBA. When talking about trading edges or gain expectancy, market participants default to the arithmetic gain expectancy. It is easy to grasp and calculate. The simplicity of this formula imposes itself, even to those who do not understand its sophistication. 
    # Expectancy formula, win_rate is your Hit ratio, avg_win is the average gain per trade, and avg_loss is the average loss per trade
def expectancy...
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Authors (1)

Profile icon Laurent Bernut
LinkedIn
Laurent Bernut has 2 decades of experience in alternative investment space. After the US CPA, he compiled financial statements in Japanese and English for a Tokyo Stock Exchange-listed corporation. After serving as an analyst in two Tokyo-based hedge funds, he joined Fidelity Investments Japan as a dedicated quantitative short-seller. Laurent has built numerous portfolio management systems and developed several quantitative models across various platforms. He currently writes and runs algorithmic strategies and is an undisputed authority on short selling on Quora, where he was nominated top writer for 2017, 2018, and 2019.
Read more
See other products by Laurent Bernut

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