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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

Chapter 6. Trading Using Google Trends

Several years ago, a paper titled Quantifying Trading Behavior in Financial Markets Using Google Trends was published in Scientific Reports. This paper asked this question: "Is it possible to predict efficient trading strategies based upon the frequency of certain words in Google searches?"

The authors went through a number of interesting steps involved in gathering data and performing analyses. They derived a set of financial keywords from the Financial Times website that they thought were good words for examining patterns of search for financial information.

With this, they built a robust set of keywords using Google Sets (which is now defunct). Using those keywords, they collected Google Trends data on those words over a period of years and defined a trading execution plan to buy or sell based upon the changes in the search history on all of their terms. They ran the strategies for all the keywords and ranked the value of their...

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