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...

#### Introduction to R for Quantitative Finance

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#### Introduction to R for Quantitative Finance

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#### 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

Free Chapter

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

Customer Reviews