Book Image

Introduction to R for Quantitative Finance

By : Gergely Daróczi, Michael Puhle, Edina Berlinger (EURO), Daniel Daniel Havran, Kata Váradi, Agnes Vidovics-Dancs, Agnes Vidovics Dancs, Michael Phule, Zsolt Tulassay, Peter Csoka, Marton Michaletzky, Edina Berlinger (EURO), Varadi Kata
Book Image

Introduction to R for Quantitative Finance

By: Gergely Daróczi, Michael Puhle, Edina Berlinger (EURO), Daniel Daniel Havran, Kata Váradi, Agnes Vidovics-Dancs, Agnes Vidovics Dancs, Michael Phule, Zsolt Tulassay, Peter Csoka, Marton Michaletzky, Edina Berlinger (EURO), Varadi Kata

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

Tangency portfolio and Capital Market Line


What happens when a riskless asset is added to the model? If and X is any risky portfolio, then and obviously, . This means that those portfolios form a straight line on the mean-standard deviation plane. Any portfolio on this line is available by investing into R and X. It is clear that the best choice for X is the point where this line is tangent to Efficient Frontier. This tangency point is called the market portfolio or tangency portfolio, and the tangent of Efficient Frontier of risky assets at this point is called Capital Market Line (CML), which consists of the efficient portfolios of all the assets in this case. The last question that we address regarding the mean-variance model is how the market portfolio (or equivalently, the CML) can be determined.

We can easily modify the variance minimization code to accomplish this. First of all, if we add a riskless asset, a full-zero row and column is added to the covariance matrix (where n is...