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 rebalancing


Dynamic rebalancing is a process of keeping one's portfolio closer to your allocated target using the natural cash inflows and outflows to your portfolio. Rebalancing involves periodically buying or selling assets in a portfolio to maintain an original desired level of asset allocation, realigning the weightings of a portfolio of assets.

Let us consider an example. In a portfolio, the target asset allocation was 40% stocks and 60% bonds. If the bonds performed well during the period, the weights of bonds in the portfolio could result to 70%. Then, the investor will decide to sell some bonds and buy some stocks to get the portfolio back to the original target allocation of 40% stock and 60% bonds.

Now, let us see how to do rebalancing of the portfolio in R.

Periodic rebalancing

Let us consider data sourced from R:

>library(PerformanceAnalytics) 
>data(edhec)  
> data<-edhec["1999", 3:5] 
> colnames(data) = c("DS","EM","EMN") 
> data 
...