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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, first we have explained many basic concepts related to portfolio theory, such as covariance,correlation, the formulas on how to calculate variance of a 2-stock portfolio and variance of an n-stock portfolio. After that, we have discussed 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 setup an objective function, how to choose an efficient portfolio for a given set of stocks, and how to construct an efficient frontier.

In the next chapter, we will discuss one of the most important theory in modern finance: options and futures. We will start from the basic concepts such as payoff functions for a call and for a put. Then we explain the related applications such as various trading strategies, corporate incentive plans, and hedging strategies including different types of options and futures.

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