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Learning Quantitative Finance with R (Paperback)
Loot Price: R1,363
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Learning Quantitative Finance with R (Paperback)
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Implement machine learning, time-series analysis, algorithmic
trading and more 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.
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