Introduction to R for Quantitative Finance
eBook - ePub

Introduction to R for Quantitative Finance

Gergely Daroczi, Michael Puhle, Edina Berlinger, Peter Csoka, Daniel Havran, Marton Michaletzky, Zsolt Tulassay, Kata Varadi, Agnes Vidovics-Dancs

  1. 164 páginas
  2. English
  3. ePUB (apto para móviles)
  4. Disponible en iOS y Android
eBook - ePub

Introduction to R for Quantitative Finance

Gergely Daroczi, Michael Puhle, Edina Berlinger, Peter Csoka, Daniel Havran, Marton Michaletzky, Zsolt Tulassay, Kata Varadi, Agnes Vidovics-Dancs

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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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Información

Año
2013
ISBN
9781783280933
Edición
1
Categoría
Informatica

Introduction to R for Quantitative Finance


Table of Contents

Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers and more
Why Subscribe?
Free Access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. Time Series Analysis
Working with time series data
Linear time series modeling and forecasting
Modeling and forecasting UK house prices
Model identification and estimation
Model diagnostic checking
Forecasting
Cointegration
Cross hedging jet fuel
Modeling volatility
Volatility forecasting for risk management
Testing for ARCH effects
GARCH model specification
GARCH model estimation
Backtesting the risk model
Forecasting
Summary
2. Portfolio Optimization
Mean-Variance model
Solution concepts
Theorem (Lagrange)
Working with real data
Tangency portfolio and Capital Market Line
Noise in the covariance matrix
When variance is not enough
Summary
3. Asset Pricing Models
Capital Asset Pricing Model
Arbitrage Pricing Theory
Beta estimation
Data selection
Simple beta estimation
Beta estimation from linear regression
Model testing
Data collection
Modeling the SCL
Testing the explanatory power of the individual variance
Summary
4. Fixed Income Securities
Measuring market risk of fixed income securities
Example – implementation in R
Immunization of fixed income portfolios
Net worth immunization
Target date immunization
Dedication
Pricing a convertible bond
Summary
5. Estimating the Term Structure of Interest Rates
The term structure of interest rates and related functions
The estimation problem
Estimation of the term structure by linear regression
Cubic spline regression
Applied R functions
Summary
6. Derivatives Pricing
The Black-Scholes model
The Cox-Ross-Rubinstein model
Connection between the two models
Greeks
Implied volatility
Summary
7. Credit Risk Management
Credit default models
Structural models
Intensity models
Correlated defaults – the portfolio approach
Migration matrices
Getting started with credit scoring in R
Summary
8. Extreme Value Theory
Theoretical overview
Application – modeling insurance claims
Exploratory data analysis
Tail behavior of claims
Determining the threshold
Fitting a GPD distribution to the tails
Quantile estimation using the fitted GPD model
Calculation of expected loss using the fitted GPD model
Summary
9. Financial Networks
Representation, simulation, and visualization of financial networks
Analysis of networks’ structure and detection of topology changes
Contribution to systemic risk – identification of SIFIs
Summary
A. References
Time series analysis
Portfolio optimization
Asset pricing
Fixed income securities
Estimating the term structure of interest rates
Derivatives Pricing
Credit risk management
Extreme value theory
Financial networks
Index

Introduction to R for Quantitative Finance

Copyright © 2013 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: November 2013
Production Reference: 1151113
Published by Packt Publishing Ltd.
Livery Place
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Birmingham B3 2PB, UK..
ISBN 978-1-78328-093-3
www.packtpub.com
Cover Image by Suresh Mogre ()

Credits

Authors
Gergely Daróczi
Michael Puhle
Edina Berlinger
Péter Csóka
Dániel Havran
Márton Michaletzky
Zsolt Tulassay
Kata Váradi
Agnes Vidovics-Dancs
Reviewers
Dr. Hari Shanker Gupta
Ronald Hochreiter
Acquisition Editor
Akram Hussain
Lead Technical Editor
Mohammed Fahad
Technical Editors
Venu Manthena
Adrian Raposo
Amit Singh
Copy Editors
Alisha Aranha
Tanvi Gaitonde
Sayanee...

Índice

  1. Introduction to R for Quantitative Finance
Estilos de citas para Introduction to R for Quantitative Finance

APA 6 Citation

Daroczi, G., Puhle, M., Berlinger, E., Csoka, P., Havran, D., Michaletzky, M., … Vidovics-Dancs, A. (2013). Introduction to R for Quantitative Finance (1st ed.). Packt Publishing. Retrieved from https://www.perlego.com/book/390361/introduction-to-r-for-quantitative-finance-pdf (Original work published 2013)

Chicago Citation

Daroczi, Gergely, Michael Puhle, Edina Berlinger, Peter Csoka, Daniel Havran, Marton Michaletzky, Zsolt Tulassay, Kata Varadi, and Agnes Vidovics-Dancs. (2013) 2013. Introduction to R for Quantitative Finance. 1st ed. Packt Publishing. https://www.perlego.com/book/390361/introduction-to-r-for-quantitative-finance-pdf.

Harvard Citation

Daroczi, G. et al. (2013) Introduction to R for Quantitative Finance. 1st edn. Packt Publishing. Available at: https://www.perlego.com/book/390361/introduction-to-r-for-quantitative-finance-pdf (Accessed: 14 October 2022).

MLA 7 Citation

Daroczi, Gergely et al. Introduction to R for Quantitative Finance. 1st ed. Packt Publishing, 2013. Web. 14 Oct. 2022.