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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 examined several techniques for using pandas to calculate the prices of options, their payoffs, and the profit and loss for the various combinations of calls and puts for both buyers and sellers. We started with a brief introduction to options, covered how to load current market data for options from Yahoo! Finance, and then examined the properties of the data retrieved from the web services.

We then examined the pricing of options using Black-Scholes with a brief explanation of how the algorithm models option prices. We also used the Mibian library to calculate prices using Black-Scholes. We finished with a brief explanation of the Greeks and how to calculate their values for various configurations of options.

In the next chapter, we will look at the modeling of investment portfolios using Python and pandas and how we can calculate optimal portfolios that balance risk and return for different investor types.

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