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Mastering Python for Finance

You're reading from   Mastering Python for Finance Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781784394516
Length 340 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Python for Financial Applications FREE CHAPTER 2. The Importance of Linearity in Finance 3. Nonlinearity in Finance 4. Numerical Procedures 5. Interest Rates and Derivatives 6. Interactive Financial Analytics with Python and VSTOXX 7. Big Data with Python 8. Algorithmic Trading 9. Backtesting 10. Excel with Python Index

Chapter 6. Interactive Financial Analytics with Python and VSTOXX

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) measures the short-term volatility implied by S&P 500 stock index option prices. Many people around the world use the VIX to measure the stock market volatility over the next 30-day period. In Europe, the EURO STOXX 50 Volatility (VSTOXX) market index is based on the market prices of a basket of Euro STOXX 50 Index Options (OESX) and measures the implied market volatility over the next 30 days on the EURO STOXX 50 Index. For benchmark strategies utilizing the EURO STOXX 50 Index, the nature of its negative correlation with the VSTOXX presents a viable way of avoiding...

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