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Learning Quantitative Finance with R

You're reading from   Learning Quantitative Finance with R Implement machine learning, time-series analysis, algorithmic trading and more

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786462411
Length 284 pages
Edition 1st Edition
Languages
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Authors (2):
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PRASHANT VATS PRASHANT VATS
Author Profile Icon PRASHANT VATS
PRASHANT VATS
Dr. Param Jeet Dr. Param Jeet
Author Profile Icon Dr. Param Jeet
Dr. Param Jeet
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to R FREE CHAPTER 2. Statistical Modeling 3. Econometric and Wavelet Analysis 4. Time Series Modeling 5. Algorithmic Trading 6. Trading Using Machine Learning 7. Risk Management 8. Optimization 9. Derivative Pricing

Questions

  1. What are the packages to be used for option, bond, and exotic options pricing?
  2. Which functions will you use to calculate the option price using the Black-Scholes and Cox-Ross-Rubinstein methods?
  3. How does the CRR price converge to the binomial price and which command would you use to calculate Greeks?
  4. Write a command to calculate implied volatility.
  5. How would you prepare a cashflow and maturity matrix to the form which would be used in bond pricing function, and which function would be used for bond pricing?
  6. What are the functions to be used for credit spread and credit default swaps?
  7. What are the Asian option types, barrier option types, and digital option types?
  8. What are the functions you would use for the options in question 7?
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