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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, many concepts and issues associated with time-series are discussed in detail. Topics include how to design a true date variable, how to merge datasets with different frequencies, how to download historical prices from Yahoo! Finance; also, different ways to estimate returns, estimate the Roll (1984) spread, Amihud's (2002) illiquidity, Pastor and Stambaugh's (2003) liquidity, and how to retrieve high-frequency data from Prof. Hasbrouck's TORQ database (Trade, Oder, Report and Quotation). In addition, two datasets from CRSP are shown. Since this book is focusing on open and publicly available finance, economics, and accounting data, we could mention a few financial databases superficially.

In the next chapter, we discuss many concepts and theories related to portfolio theory such as how to measure portfolio risk, how to estimate the risk of 2-stock and n-stock portfolio, the trade-off between risk and return by using various measures of Sharpe ratio...

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