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

Momentum or directional trading


Momentum trading is trading when the instrument is trending up or down or, in other words, continuation in the trend as like historical winners are expected to be winners and historical losers are expected to lose. You bet on the direction of the instrument and you aim for buying at a low price and selling at a high price. I will not cover the pros and cons and what the different types of momentum trading strategies are. It is left to the trader to devise any idea. I will cover how to implement momentum trading rules and backtest using historical data in R. Stock return depends on various factors, and later in this chapter, I will show you how to use the multifactor model which explains stock return.

Let me start with simple technical indicators.

Technical indicators are implemented in the quantmod package so I will be using quantmod for this:

> library('quantmod') 
>getSymbols("^DJI",src="yahoo") 
[1] "DJI" 
> head(DJI) 

We have...