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Mastering Pandas for Finance

You're reading from   Mastering Pandas for Finance Master pandas, an open source Python Data Analysis Library, for financial data analysis

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Product type Paperback
Published in May 2015
Publisher Packt
ISBN-13 9781783985104
Length 298 pages
Edition 1st Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with pandas Using Wakari.io FREE CHAPTER 2. Introducing the Series and DataFrame 3. Reshaping, Reorganizing, and Aggregating 4. Time-series 5. Time-series Stock Data 6. Trading Using Google Trends 7. Algorithmic Trading 8. Working with Options 9. Portfolios and Risk Index

Summary


In this chapter, we took an adventure into learning the fundamentals of algorithmic trading using pandas and Zipline. We started with a little theory to set a framework for understanding how the algorithms would be implemented. From there, we implemented three different trading algorithms using Zipline and dived into the decisions made and their impact on the portfolios as the transactions were executed. Finally, we established a fundamental knowledge of how to simulate markets and make automated trading decisions.

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