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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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Toc

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

Calculating the VIX Index

In this section, we will perform a step-by-step replication of the VIX Index. Calculation of the VIX Index is documented on the CBOE website. You may obtain a copy of the CBOE VIX white paper at http://www.cboe.com/micro/vix/vixwhite.pdf.

Importing SPX options data

Suppose you had gathered SPX options data from your broker or purchased historical data from an external source such as the CBOE website. For the purpose of this chapter, the end-of-day SPX option chain prices are observed from Monday, October 15, 2018 to Friday, October 19, 2018 and saved into Comma-separated Values (CSV) files. Sample copies of these files are provided under the files folder of the source codes repository.

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