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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 simplest definition of a VaR? What are the differences between a VaR and variance and standard deviation and beta?
  2. Assume that we have a plan to form a two-stock portfolio. The confidence level is 99% and number of period is 10 days. If the VaR for the first stock is x while the VaR for the second stock is y, is the portfolio VaR the weighted individual stock's VaR, that is, VaR(portfolio) = wA*x + wB*y, where WA is the weight for stock A while wB is the weight for stock B? Explain.
  3. Do IBM's returns follow a normal distribution? Are their skewness and kurtosis zero and 3 (excess kurtosis is zero)?
  4. What are the values of skewness and kurtosis for a normal distribution? Generate n random numbers by using rnorm() to support your conclusion.
  5. Write a Python function to estimate mean, standard deviation, skewness, and kurtosis of a given ticker; for example, moments4("ticker",begdate,enddate).
  6. Assuming that we own 134 shares of Microsoft; what is the total...
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