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

Summary


This chapter used derivative pricing only in terms of implementation in R, and various packages such as foptions, termstrc, CreditMetrics, credule, GUIDE, and fExoticOptions to price options, bonds, credit spreads, credit default swaps, and interest rate derivatives, and different types of exotic options were used. Derivative pricing is crucial in derivative trading and it is very important to learn it.

This chapter also covered the Black-Scholes and Cox-Ross-Rubinstein methods, along with Greeks and implied volatility for options. It also explained bond price and yield curves. It also used functions which explain how credit spread, credit default swaps, and interest rate derivatives are priced. Toward the end, it covered various types of exotic options. It used data given in relevant packages and implemented functions.