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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

Application – modeling insurance claims


In the remainder of this chapter, we work through an example of using EVT in a real-life risk management application. We apply the preceding methodology to fire insurance claims, with the aims of fitting a distribution to the tails and providing quantile estimates and conditional expectations to characterize the probability and magnitude of large fire losses. We note that the exact same steps may be applied to credit losses or operational losses as well. For market risk management problems, where the underlying data is generally the return of a security, we would remove the gains from the data set and focus on the losses only; otherwise, the modeling steps are again identical.

Multiple packages are available in R for extreme value analysis. In this chapter we present the evir package in the following command. A good overview of the various R packages for EVT is provided in Gilleland, Ribatet, and Stephenson (2013).

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