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About This Book
Understand the basics of R and how they can be applied in various Quantitative Finance scenarios
Learn various algorithmic trading techniques and ways to optimize them using the tools available in R.
Contain different methods to manage risk and explore trading using Machine Learning.
Who This Book Is For
If you want to learn how to use R to build quantitative finance models with ease, this book is for you. Analysts who want to learn R to solve their quantitative finance problems will also find this book useful. Some understanding of the basic financial concepts will be useful, though prior knowledge of R is not required.
What You Will Learn
Get to know the basics of R and how to use it in the field of Quantitative Finance
Understand data processing and model building using R
Explore different types of analytical techniques such as statistical analysis, time-series analysis, predictive modeling, and econometric analysis
Build and analyze quantitative finance models using real-world examples
How real-life examples should be used to develop strategies
Performance metrics to look into before deciding upon any model
Deep dive into the vast world of machine-learning based trading
Get to grips with algorithmic trading and different ways of optimizing it
Learn about controlling risk parameters of financial instruments
In Detail
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.
Style and approach
This book introduces you to the essentials of quantitative finance with the help of easy-to-understand, practical examples and use cases in R. Each chapter presents a specific financial concept in detail, backed with relevant theory and the implementation of a real-life example.
This is a digital product.
Learning Quantitative Finance with R 1st Edition is written by Dr. Param Jeet, Prashant Vats and published by Packt Publishing. The Digital and eTextbook ISBNs for Learning Quantitative Finance with R are 9781786465252, 1786465256 and the print ISBNs are 9781786462411, 1786462419.

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