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Mastering Python for Finance

You're reading from   Mastering Python for Finance Implement advanced state-of-the-art financial statistical applications using Python

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789346466
Length 426 pages
Edition 2nd Edition
Languages
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Author (1):
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James Ma Weiming James Ma Weiming
Author Profile Icon James Ma Weiming
James Ma Weiming
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Python
2. Overview of Financial Analysis with Python FREE CHAPTER 3. Section 2: Financial Concepts
4. The Importance of Linearity in Finance 5. Nonlinearity in Finance 6. Numerical Methods for Pricing Options 7. Modeling Interest Rates and Derivatives 8. Statistical Analysis of Time Series Data 9. Section 3: A Hands-On Approach
10. Interactive Financial Analytics with the VIX 11. Building an Algorithmic Trading Platform 12. Implementing a Backtesting System 13. Machine Learning for Finance 14. Deep Learning for Finance 15. Other Books You May Enjoy

The Dow Jones industrial average and its 30 components

The Dow Jones Industrial Average (DJIA) is a stock market index that comprises the 30 largest US companies. Commonly known as the Dow, it is owned by S&P Dow Jones Indices LLC and computed on a price-weighted basis (see https://us.spindices.com/index-family/us-equity/dow-jones-averages for more information on the Dow).

This section involves downloading the datasets of Dow and its components into pandas DataFrame objects for use in later sections of this chapter.

Downloading Dow component datasets from Quandl

The following code retrieves the Dow component datasets from Quandl. The data provider that we will be using is WIKI Prices, a community formed by members...

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