Book Image

Introduction to R for Quantitative Finance

Book Image

Introduction to R for Quantitative Finance

Overview of this book

Introduction to R for Quantitative Finance will show you how to solve real-world quantitative fi nance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to fi nancial networks. Each chapter briefl y presents the theory behind specific concepts and deals with solving a diverse range of problems using R with the help of practical examples.This book will be your guide on how to use and master R in order to solve quantitative finance problems. This book covers the essentials of quantitative finance, taking you through a number of clear and practical examples in R that will not only help you to understand the theory, but how to effectively deal with your own real-life problems.Starting with time series analysis, you will also learn how to optimize portfolios and how asset pricing models work. The book then covers fixed income securities and derivatives such as credit risk management.
Table of Contents (17 chapters)
Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


This chapter covered portfolio optimization. After presenting the main idea, we introduced the Markowitz model and its mathematical formulation. We discussed the methods for possible solutions and implemented a simple algorithm to demonstrate how these methods work on real data. We have also used pre-written R packages to solve the same problem. We broadly discussed other important subjects like the market portfolio, the uncertainty in the estimation of the covariance matrix, and the risk measures beyond variance. We hope that this was a useful first run on the topic and you are encouraged to study it further or check out the next chapter, which is about a related subject—asset pricing models.