Learning Quantitative Finance with R

Dr. Param Jeet, Prashant Vats

• Publisher: Packt Publishing
• Year: 2017
• eBook ISBN: 9781786465252
• Edition: 1
• Topic: Computer Science
• Subtopic: Computer Science General
• Index: Computer Science

Implement machine learning, time-series analysis, algorithmic trading and moreAbout 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 ForIf 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 instrumentsIn DetailThe 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 approachThis 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.

Learning Quantitative Finance with R

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Learning Quantitative Finance with R

Copyright © 2017 Packt Publishing

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First published: March 2017

Production reference: 1210317

Published by Packt Publishing Ltd.

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ISBN 978-1-78646-241-1

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Credits

Authors Dr. Param Jeet Prashant Vats	Copy Editor Safis Editing
Reviewer Manuel Amunategui	Project Coordinator Shweta H Birwatkar
Commissioning Editor Amey Varangaonkar	Proofreader Safis Editing
Acquisition Editor Varsha Shetty	Indexer Mariammal Chettiyar
Content Development Editor Amrita Noronha	Graphics Tania Dutta
Technical Editor Akash Patel	Production Coordinator Arvindkumar Gupta

About the Authors

Dr. Param Jeet is a Ph.D. in mathematics from one of India's leading technological institute in Madras (IITM), India. Dr. Param Jeet has a couple of mathematical research papers published in various international journals. Dr. Param Jeet has been into the analytics industry for the last few years and has worked with various leading multinational companies as well as consulted few of companies as a data scientist.

I would like to thank my parents, S. Dhayan Singh & Jeet Kaur, who always supported me in every phase of my life, my wife, Manpreet Kaur, who every time put herself behind me with full energy and encourage me to write book, my little boy, Kavan Singh, whose innocence and little smile always cherished me to work and all family members. I also would like to thanks my Doctorate thesis advisor, Prof. Satyajit Roy, all the mentors I've had over the years, colleagues and friends without their help this book would not have been possible. With all these, I would like to share my knowledge with everyone who is keen to learn quantitative finance using R.

Prashant Vats is a masters in mathematics from one of India’s leading technological institute, IIT Mumbai. Prashant has been into analytics industry for more than 10 years and has worked with various leading multinational companies as well as consulted few of companies as data scientist across several domain.

I would like to thank my parents, Late Devendra K. Singh & Sushila Sinha, who allowed me to follow my dreams and have always supported me throughout my career. I would like to thank my wife, Namrata for standing beside me in all phases of my life and supporting me to write this book, my little boy, Aahan Vats whose smile always inspires me . I also would like to thank all the mentors I've had over the years, co-workers and friends without their help this book would not have been possible. With all these, I would like to share my knowledge with everyone who is keen to learn quantitative finance using R.

About the Reviewer

Manuel Amunategui is an applied data scientist. He has implemented enterprise predictive solutions for many industries, including healthcare, finance, and sales. Prior to that, he worked as a quantitative developer on Wall Street for 6 years for one of the largest equity-options market-making firms, and as a software developer at Microsoft for 4 years.

He holds master degrees in Predictive Analytics from Northwestern University and in International Administration from the School for International Training.

He is currently the VP of Data Science at SpringML, a startup focused on offering advanced and predictive CRM analytics advice, dashboards, and automation. SpringML’s clients include Google Cloud Platform, Chevron, Yamaha, Tesoro, and Salesforce.

He is a data science advocate, blogger/vlogger (amunategui.github.io) and a trainer on Udemy.com and O’Reilly Media.

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• Learning Quantitative Finance with R