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

About the Reviewers

Dr. Hari Shanker Gupta is a Quantitative Research Analyst working in the area of Algorithming Trading System Development. Prior to this, he was a Post Doctoral Fellow at Indian Institute of Science (IISc), Bangalore, India. Hari has pursued his Ph.D. from Department of Mathematics, IISc, in the field of Applied Mathematics and Scientific Computation in the year 2010. Hari had completed his M.Sc. in Mathematics from Banaras Hindu University (B.H.U.), Varanasi, India. During M.Sc., Hari was awarded four gold medals for his outstanding performance in B.H.U., Varanasi.

Hari has published five research papers in reputed journals in the field of Mathematics and Scientific Computation. He has experience of working in the areas of mathematics, statistics, and computations. These include the topics: numerical methods, partial differential equation, mathematical finance, stochastic calculus, data analysis, finite difference, and finite element method. He is very comfortable with the mathematics software, Matlab; the statistics programming language, R, and, the programming language, C, and has been recently working on the Python platform.

Ronald Hochreiter is an Assistant Professor at the Department of Finance, Accounting and Statistics, at the WU Vienna University of Economics and Business. He obtained his Ph.D. in Computational Management Science at the University of Vienna in 2005. He is an avid R user and develops R packages mainly for optimization modeling purposes as well as for applications in Finance. A summary of his R projects can be found at http://www.hochreiter.net/R/, and some of his tutorials on Financial Engineering with R are online at http://www.finance-r.com/.