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Learning Quantitative Finance with R

This is the code repository for Learning Quantitative Finance with R, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.

About the 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.

By the end of this book, you will have a firm grasp of the techniques required to implement basic quantitative finance models in R.

Instructions and Navigation

All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter 02.

The code will look like the following:

    > y <- dnorm(Sampledata$Return, mean = mean(Sampledata$Return), 
    sd =sd(Sampledata$Return, na.rm = FALSE))
    > plot(Sampledata$Return,y) 

Software requirements:

Download and install R for various platforms such as Windows, Linux, and Mac. Go to the following link: https://cran.rstudio.com/. R is an open source platform and can be installed free of charge for any operating system from: https://www.r-project.org/. Installation guidelines are also found on this website.

Note:

Chapter 05, 06 and 09 does not contain dataset files. You can use the code from chapter itself.

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Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

https://packt.link/free-ebook/9781786462411

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