Introduction to R for Quantitative Finance
By Gergely Daróczi, Michael Puhle, Edina Berlinger, Péter Csóka, Daniel Havran, Márton Michaletzky, Zsolt Tulassay, Kata Váradi, Agnes Vidovics-Dancs
Publisher: Packt Publishing
Final Release Date: November 2013
Pages: 164

In Detail

Quantitative finance is an increasingly important area for businesses, and skilled professionals are highly sought after. The statistical computing language R is becoming established in universities and in industry as the lingua franca of data analysis and statistical computing.

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.

Approach

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 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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oreillyIntroduction to R for Quantitative Finance
 
3.0

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(1 of 1 customers found this review helpful)

 
3.0

Useful for Existing Users

By JamR

from London

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  • Well-written

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    Comments about oreilly Introduction to R for Quantitative Finance:

    All in all, this is an excellent book for anyone keen on learning R in a quantitative finance framework. I think it would have benefited from a formal introduction to R and a data Export/Import capabilities review but both topics are extensively covered in many other R resources...

    (2 of 2 customers found this review helpful)

     
    3.0

    Useful for existing R users

    By arsalvacion

    from Philippinbes

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    • Helpful examples

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      • Student

      Comments about oreilly Introduction to R for Quantitative Finance:

      The book around which is around 164 pages (including cover page and back pages) discuss the implementation different quantitative methods used in finance using R language. The book consists of nine (9) chapters cover topics from time series analysis to finance networks.

      For individuals with little background in quantitative methods in finance, the theoretical and application discussion in the start of each chapter provided a good overview and basics of the method being discussed. Also, the problem-solution approached used by the authors added practicality on the used of the book for quantitative analysis. However, for individuals (i.e. finance people) with little R background, the book somehow lacks the basic introduction to the R language and environment commonly found in most R books and tutorials. I think for finance individuals who are R beginners, it will be handy to use this book along with R introductory books/websites (e.g. Instant R, Quick R)

      **Disclaimer: This book was given to me for a review

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