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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. Which module contains the function called rolling_kurt? How can you use the function?
  2. Based on daily data downloaded from Yahoo! Finance, find whether Wal-Mart's daily returns follow a normal distribution.
  3. Based on daily returns in 2016, are the mean returns for IBM and DELL the same?

    Tip

    You can use Yahoo! Finance as your source of data

  4. How many dividends distributed or stock splits happened over the past 10 years for IBM and DELL based on the historical data?
  5. Write a Python program to estimate rolling beta on a 3-year window for a few stocks such as IBM, WMT, C and MSFT.
  6. Assume that we just downloaded the prime rate from the Federal Banks' data library from: http://www.federalreserve.gov/releases/h15/data.htm. We downloaded the time-series for Financial 1-month business day. Write a Python program to merge them using:
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