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Introduction to R for Quantitative Finance

You're reading from  Introduction to R for Quantitative Finance

Product type Book
Published in Nov 2013
Publisher Packt
ISBN-13 9781783280933
Pages 164 pages
Edition 1st Edition
Languages

Table of Contents (17) Chapters

Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Time Series Analysis Portfolio Optimization Asset Pricing Models Fixed Income Securities Estimating the Term Structure of Interest Rates Derivatives Pricing Credit Risk Management Extreme Value Theory 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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