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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 9. Portfolio Theory

Understanding portfolio theory is very important in learning finance. It is well known that don't put all your eggs in one basket, that is, it is a great idea to diversify away your risk. However, very few know the implied assumption behind such a famous idiom. In this chapter, we will discuss various risk measures for individual stocks or portfolios, such as Sharpe ratio, Treynor ratio, Sortino ratio, how to minimize portfolio risk based on those measures (ratios), how to set up an objective function, how to choose an efficient portfolio for a given set of stocks, and how to construct an efficient frontier. Our focus is on how to apply portfolio theory by using real-world data. For instance, today we have $2 million cash and plan to purchase IBM and Walmart stocks. If we have 30% invested in the first one and the rest in the second, what is our portfolio risk? What is the least risky portfolio that we could form based on those two stocks? How...

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