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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

Lower partial standard deviation and Sortino ratio

We discussed this concept already. However, for completeness, in this chapter we mention it again. One issue with using standard deviation of returns as a risk measure is that the positive deviation is also viewed as bad. The second issue is that the deviation is from the average instead of a fixed benchmark, such as a risk-free rate. To overcome these shortcomings, Sortino (1983) suggests the lower partial standard deviation, which is defined as the average of squared deviation from the risk-free rate conditional on negative excess returns, as shown in the following formula:

Lower partial standard deviation and Sortino ratio

Because we need the risk-free rate in this equation, we could generate a Fama-French dataset that includes the risk-free rate as one of their time series. First, download their daily factors from http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html. Then, unzip it and delete the non-data part at the end of the text file. Assume the final text file...

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