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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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Toc

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

Exercises

  1. What is the definition of volatility?
  2. How can you measure risk (volatility)?
  3. What are the issues related to the widely used definition of risk (standard deviation)?
  4. How can you test whether stock returns follow a normal distribution? For the following given set of stocks, test whether they follow a normal distribution:

    Company name

    Ticker

    Dell company

    DELL

    International Business Machine

    IBM

    General Electric

    GE

    Microsoft

    MSFT

    Google

    GOOG

    Family Dollar Stores

    FDO

    Apple

    AAPL

    Wal-Mart Stores

    WMT

    eBay

    EBAY

    McDonald's

    MCD

      
  5. What is the lower partial standard deviation? What are its applications?
  6. Choose five stocks, such as DELL, IBM, Microsoft, Citi Group, and Walmart, and compare their standard deviation with LPSD based on the last three-years' daily data.
  7. Is a stock's volatility constant over the years? You could choose International Business Machine (IBM) and Walmart (WMT) to test your hypothesis.
  8. What is an ARCH (1) process?
  9. What is a GARCH...
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