Book Image

Learning Quantitative Finance with R

By : Dr. Param Jeet, PRASHANT VATS
Book Image

Learning Quantitative Finance with R

By: Dr. Param Jeet, PRASHANT VATS

Overview of this book

The role of a quantitative analyst is very challenging, yet lucrative, so there is a lot of competition for the role in top-tier organizations and investment banks. This book is your go-to resource if you want to equip yourself with the skills required to tackle any real-world problem in quantitative finance using the popular R programming language. You'll start by getting an understanding of the basics of R and its relevance in the field of quantitative finance. Once you've built this foundation, we'll dive into the practicalities of building financial models in R. This will help you have a fair understanding of the topics as well as their implementation, as the authors have presented some use cases along with examples that are easy to understand and correlate. We'll also look at risk management and optimization techniques for algorithmic trading. Finally, the book will explain some advanced concepts, such as trading using machine learning, optimizations, exotic options, and hedging. By the end of this book, you will have a firm grasp of the techniques required to implement basic quantitative finance models in R.
Table of Contents (16 chapters)
Learning Quantitative Finance with R
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Dynamic conditional correlation


Multivariate GARCH models, which are linear in squares and cross products of the data, are generally used to estimate the correlations changing with time. Now this can be estimated using dynamic conditional correlation (DCC), which is a combination of a univariate GARCH model and parsimonious parametric models for the correlation. It has been observed that they perform well in a variety of situations. This method has the flexibility of univariate GARCH and does not have the complexity of multivariate GARCH.

Now let us see how to execute DCC in R.

First we need to install and load the packages rmgarch and PerformanceAnalytics. This can be done by executing the following code:

install.packages("rmgarch") 
install.packages("PerformanceAnalytics") 
library(rmgarch) 
library(PerformanceAnalytics) 

Now let us consider returns of the last year for the S&P 500 and DJI indexes and try to get DCC for these returns.

Now let us set the specification for DCC by executing...