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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 2. Portfolio Optimization FREE CHAPTER 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

Applied R functions


Although we have already used some functions from the termstrc package in the previous example to demonstrate how one can determine the ideal number of knot points and also specify those, this process can be done in an easier manner with some further R functions, as shown in the following command lines:

> x <- estim_cs(govbonds, 'GERMANY')
> x$knotpoints[[1]]
       DE0001135101 DE0001141463 DE0001135218 DE0001135317              
0.0000     1.006027     2.380274     5.033425     9.234521 31.44657

First we used the estim_cs function that estimates the term structure of coupon bonds based on cubic splines (Ferstl-Haydn, 2010) and returns the knot points in a list with the knotpoints name. Please note that estim_cs works with a list—just like most functions in the package—that's why x$knotpoints returned a list from which we checked only the first element that was identical to the values we computed manually in the preceding section.

There are a bunch of other useful...

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