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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 briefly introduced some of the most common methods related to credit risk modeling. However, there are several industrial approaches for handling default risk. The bases of the advanced methods are usually some of the structural and intensity-based approaches. Copula models are still popular for modeling the risk of credit portfolios, especially in the pricing of structured credit derivatives. There are comprehensive and strong R packages for modeling copulas. The first step to model downgrade risk is knowledge about the principles of managing migration matrices and the CreditMetrics approach. Finally, we briefly outlined the possibilities of credit scoring in R.

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