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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

Summary


This chapter used derivative pricing only in terms of implementation in R, and various packages such as foptions, termstrc, CreditMetrics, credule, GUIDE, and fExoticOptions to price options, bonds, credit spreads, credit default swaps, and interest rate derivatives, and different types of exotic options were used. Derivative pricing is crucial in derivative trading and it is very important to learn it.

This chapter also covered the Black-Scholes and Cox-Ross-Rubinstein methods, along with Greeks and implied volatility for options. It also explained bond price and yield curves. It also used functions which explain how credit spread, credit default swaps, and interest rate derivatives are priced. Toward the end, it covered various types of exotic options. It used data given in relevant packages and implemented functions.

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