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Learning Quantitative Finance with R

You're reading from  Learning Quantitative Finance with R

Product type Book
Published in Mar 2017
Publisher Packt
ISBN-13 9781786462411
Pages 284 pages
Edition 1st Edition
Languages
Authors (2):
Dr. Param Jeet Dr. Param Jeet
Profile icon Dr. Param Jeet
PRASHANT VATS PRASHANT VATS
Profile icon PRASHANT VATS
View More author details

Table of Contents (16) Chapters

Learning Quantitative Finance with R
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to R 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

Implied volatility


In option trading, we calculated volatility as historical volatility and implied volatility. Historical volatility is the price deviation in the past one year while implied volatility, on the other hand, is calculated using option price and implies stock volatility in the future. Implied volatility is crucial in option trading as it gives the future estimate of stock volatility. European call option implied volatility can be calculated using EuropeanOptionImpliedVolatility(), as shown in the following code. The first parameter is type of option, the second is call or put price, the third and fourth are current price of underlying and strike price of option, the fifth is dividend yield, and the sixth, seventh, and eighth parameters are risk-free rate of return, time to maturity in years, and initial guess for volatility:

>iv  <-EuropeanOptionImpliedVolatility("call", 11.10, 100, 100, 0.01, 0.03, 0.5,0.4) 
> iv 
[1] 0.3805953 

Similarly, implied volatility for the...

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