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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

Correlated defaults – the portfolio approach


In this section, we show you how to deal with correlated random variables with copulas for the simulation of loss distributions of credit portfolios. The copula function is a joint cumulative distribution function of uniform distributed random variables. The copula function contains all the information on the dependence structure of the components. Any of the continuously distributed random variables can be transformed into uniformly distributed variables, which allows for the possibility of general modeling; for example, it can be combined with the structural approach. Using the copula package, we demonstrate how to simulate two uniformly distributed random variables with Gaussian and t-copulas, and how to fit in a Gaussian copula parameter from the generated data. (One can apply this method for historical datasets also.) This package also serves useful functions in a wide range of topics about copulas, such as plotting or fitting copula classes...

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