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Introduction to R for Quantitative Finance

Introduction to R for Quantitative Finance

3.2 (20)
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Introduction to R for Quantitative Finance

Introduction to R for Quantitative Finance

3.2 (20)

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)
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Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
2
Index

Summary


In this chapter, we discussed term structure estimation methods by cubic spline regression and also demonstrated how one can estimate the term structure of interest rates in R. After a brief theoretical introduction to term structure and interest rates, also discussing the most basic methods such as a linear regression model and related problems, the chapter gave a detailed overview of an R implementation of cubic spline regression model and also mentioned already published R functions and packages for such tasks with more complex expectations.

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