R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.
Introduction to R for Quantitative Finance will show you how to solve real-world quantitative finance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to financial networks. Each chapter briefly 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 real-world 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 like credit risk management. The last chapters of this book will also provide you with an overview of exciting topics like extreme values and network analysis in quantitative finance.
What you will learn from this book
This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance.
Who this book is written for
If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.
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Gergely Daróczi is a Ph.D. candidate in Sociology with around eight years' experience in data management and analysis tasks within the R programming environment. Besides teaching Statistics at different Hungarian universities and doing data analysis jobs for several years, Gergely has founded and coordinated a UK-based online reporting startup company recently. This latter software or platform as a service which is called rapporter.net will potentially provide an intuitive frontend and an interface to all the methods and techniques covered in the book. His role in the book was to provide R implementation of the QF problems and methods.
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