The R materials are available from our public GitHub repository. To see what is available, follow the chapter links below. For each chapter a README is displayed which summarizes the available R scripts. You can download individual files by following the links to the raw versions. You can also download the complete GitHub repository as a zip file.

### R scripts by chapter

- Chapter 1: An Introduction to R Programming
- Chapter 2: Basic Concepts in Risk Management
- Chapter 3: Empirical Properties of Financial Data
- Chapter 4: Financial Time Series
- Chapter 5: Extreme Value Theory
- Chapter 6: Multivariate Models
- Chapter 7: Copulas and Dependence
- Chapter 8: Aggregate Risk
- Chapter 9: Market Risk
- Chapter 10: Credit Risk
- Chapter 11: Portfolio Credit Risk Management
- Chapter 12: Portfolio Credit Derivatives
- Chapter 13: Operational Risk and Insurance Analytics
- Chapter 14: Multivariate Time Series

### How to use the R scripts

- You will need to have R installed on your computer (see below).
- Many scripts require additional R packages. This will typically be indicated in the first few lines of the script by a
`library`

statement, e.g.`library(qrmtools)`

. Most of the packages we use are available on CRAN (including qrmtools and qrmdata). - To install a package from CRAN a command like
`install.packages("qrmtools")`

will generally work. - The packages (and R scripts presented) are under constant development. It might thus be required to install the latest version of qrmtools from R-Forge. To this end, a command like
`install.packages("qrmtools", repos = "http://R-Forge.R-project.org")`

will generally work. Should there be any problem, download the source code from this directory and compile. Type`?install.packages`

at the R command line for more information. - Links to some of the R packages we use may be found on this page.

### Getting started with R

To download R and find documentation and FAQs, please visit The R Project for Statistical Computing.

RStudio provides a free open-source IDE, which also serves as a convenient GUI for users,

R is available as Free Software under the terms of the Free Software Foundation's GNU General Public License in source code form. It compiles and runs on Windows, MacOS and a wide variety of UNIX platforms.