Book Image

Introduction to R for Quantitative Finance

Book Image

Introduction to R for Quantitative Finance

Overview of this book

Introduction to R for Quantitative Finance will show you how to solve real-world quantitative fi nance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to fi nancial networks. Each chapter briefl y presents the theory behind specific concepts and deals with solving a diverse range of problems using R with the help of practical examples.This book will be your guide on how to use and master R in order to solve quantitative finance problems. This book covers the essentials of quantitative finance, taking you through a number of clear and practical examples in R that will not only help you to understand the theory, but how to effectively deal with your own real-life problems.Starting with time series analysis, you will also learn how to optimize portfolios and how asset pricing models work. The book then covers fixed income securities and derivatives such as credit risk management.
Table of Contents (17 chapters)
Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


In this chapter, we presented a case study of how Extreme Value Theory methods can be used in R in a real-life risk management application. After briefly covering the theory of threshold exceedance models in EVT, we worked through a detailed example of fitting a model to the tails of the distribution of fire insurance claims. We used the fitted model to calculate high quantiles (Value at Risk) and conditional expectations (Expected Shortfall) for the fire losses. The presented methods are readily extendable to market, credit, or operational risk losses as well.