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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

Fama-French-Carhart four-factor model and Fama-French five-factor model

Jegadeesh and Titman (1993) show a profitable momentum trading strategy: buy winners and sell losers. The basic assumption is that within a short time period, such as 6 months, a winner will remain as a winner, while a loser will remain as a loser. For example, we could classify winners from losers based on the last 6-month cumulative total returns. Assume we are in January 1965. The total returns over the last 6 months are estimated first. Then sort them into 10 portfolios according to their total returns from the highest to the lowest. The top (bottom) 10% are labeled as winners (losers). We long winner portfolio and short loser portfolio with a 6-month holding period. The next month, February 1965, we repeat the same procedure. Over January 1965 to December 1989, Jegadeesh and Titman's (1993) empirical results suggest that such a trading strategy would generate a return of 0.95% per month. Based on this result...

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