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Introduction to R for Quantitative Finance

You're reading from   Introduction to R for Quantitative Finance R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.

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Product type Paperback
Published in Nov 2013
Publisher Packt
ISBN-13 9781783280933
Length 164 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (17) Chapters Close

Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Time Series Analysis FREE CHAPTER 2. Portfolio Optimization 3. Asset Pricing Models 4. Fixed Income Securities 5. Estimating the Term Structure of Interest Rates 6. Derivatives Pricing 7. Credit Risk Management 8. Extreme Value Theory 9. Financial Networks References Index

Summary


In this chapter, we have used R to price plain vanilla options with the Black-Scholes and Cox-Ross-Rubinstein models. Furthermore, we examined the basic Greeks and the implied volatility of these options. For more details on the financial background of these topics, see (Hull, 2011). Besides getting to know some tools from the fOptions package, we have also created a few loops and custom functions programmatically for simulation purposes. The next chapter will concentrate on how to manage credit risks by various models such as choosing an optimal credit portfolio with Monte-Carlo simulation and credit scoring methods.

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