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Python for Finance

You're reading from   Python for Finance Apply powerful finance models and quantitative analysis with Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Length 586 pages
Edition 2nd Edition
Languages
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (17) Chapters Close

Preface 1. Python Basics FREE CHAPTER 2. Introduction to Python Modules 3. Time Value of Money 4. Sources of Data 5. Bond and Stock Valuation 6. Capital Asset Pricing Model 7. Multifactor Models and Performance Measures 8. Time-Series Analysis 9. Portfolio Theory 10. Options and Futures 11. Value at Risk 12. Monte Carlo Simulation 13. Credit Risk Analysis 14. Exotic Options 15. Volatility, Implied Volatility, ARCH, and GARCH Index

Summary

In this chapter, an important risk measure called the Value at Risk (VaR) was discussed in detail. To estimate the VaR for individual stocks or portfolios, the two most popular methods are explained: based on the normality assumption and based on the sorting of historical returns. In addition, we have discussed the modified VaR method which considers the third and fourth moments in addition to the first two moments of returns. In Chapter 12, Monte Carlo Simulation, we explain how to apply simulation to finance, such as simulating stock price movements and returns, replicating the Black-Scholes-Merton options model, and pricing some exotic options.

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