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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

Interactive Financial Analytics with the VIX

Investors use volatility derivatives to diversify and hedge their risk in equity and credit portfolios. Since long-term investors in equity funds are exposed to downside risk, volatility can be used as a hedge for the tail risk and replacement for the put options. In the United States, the Chicago Board Options Exchange (CBOE) Volatility Index (VIX), or simply called the VIX, measures the short-term volatility implied by S&P 500 stock index options with an average expiration of 30 days. Many people around the world use the VIX to measure stock market volatility over the next 30-day period. In Europe, the equivalent volatility counterpart indicator is the EURO STOXX 50 Volatility (VSTOXX) Market Index. For benchmark strategies utilizing the S&P 500 Index, the nature of its negative correlation with the VIX presents a viable way...

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