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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

Exercises

  1. If the APR is 5% compounded quarterly, what is its equivalent continuously compounded rate?
  2. The value of a portfolio is $4.77 million today with a beta of 0.88. If the portfolio manager explains the market will surge in the next three months and s/he intends to increase her/ his portfolio beta from 0.88 to 1.20 in just three months by using S&P500 futures, how many contracts should s/he long or short? If the S&P500 index increases by 70 points what will be her/his gain or loss? How about if the S&P500 falls by 50 points instead?
  3. Write a Python program to price a call option.
  4. Explain the empty shell method when writing a complex Python program.
  5. Explain the logic behind the so-called comment-all-out method when writing a complex Python program.
  6. Explain the usage of the return value when we debug a program.
  7. When we write the CND (cumulative standard normal distribution), we could define a1, a2, a3, a4, and a5 separately. What are the differences between the following two approaches...
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