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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

Chapter 7. Credit Risk Management

This chapter introduces some useful tools for credit risk management. Credit risk is the distribution of the financial losses due to unexpected changes in the credit quality of a counterparty in a financial agreement (Giesecke 2004). Several tools and industrial solutions were developed for managing credit risk. In accordance with the literature, one may consider credit risk as the default risk, downgrade risk, or counterparty risk. In most cases, the default risk is related directly to the risk of non-performance of a claim or credit. In contrast, downgrade risk arises when the price of a bond declines due to its worsening credit rating without any realized credit event. Counterparty risk means the risk when the counterparty of a contract does not meet the contractual obligations. However, the contractual or regulatory definition of a credit event can usually be wider than just a missed payment. The modeling end estimation of the possibility of default...

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