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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

Chapter 7. Multifactor Models and Performance Measures

In Chapter 6, Capital Asset Pricing Model, we discussed the simplest one-factor linear model: CAPM. As mentioned, this one-factor linear model serve as a benchmark for more advanced and complex models. In this chapter, we will focus on the famous Fama-French three-factor model, Fama-French-Carhart four-factor model, and Fama-French five-factor model. After understanding those models, readers should be able to develop their own multifactor linear models, such as by adding Gross Domestic Product (GDP), Consumer Price Index (CPI), a business cycle indicator or other variables as an extra factor(s). In addition, we will discuss performance measures, such as the Sharpe ratio, Treynor ratio, and Jensen's alpha. In particular, the following topics will be covered in this chapter:

  • Introduction to the Fama-French three-factor model
  • Fama-French-Carhart four-factor model
  • Fama-French five-factor model
  • Other multiplefactor models
  • Sharpe...
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