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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
Languages
Tools
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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

Algo trading with Zipline


Zipline is a very powerful tool with many options, most of which we will not be able to investigate in this book. It makes creating trading algorithms and their simulation on historical data very easy (but there is still some creativity required).

Zipline provides several operational models. One allows the execution of Python script files via the command line. We will exclusively use a model where we include Zipline into our pandas application and request it to run our algorithms.

To do this, we will need to implement our algorithms and instruct Zipline on how to run them. This is actually a very simple process, and we will walk through implementing three algorithms of increasing complexity: buy apple, dual moving average crossover, and pairs trade.

The algorithms that we will implement have been discussed earlier: the dual moving average crossover and the pairs trading mean-reversion algorithm. We will, however, start with a very simple algorithm, buy apple, which...

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