Financial Risk Modelling and Portfolio Optimization with R

ISBN-10: 0470978708

ISBN-13: 9780470978702

Edition: 2013

Authors: Bernhard Pfaff

List price: $66.95
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Introduces the latest techniques advocated for measuring financial market risk and portfolio optimisation, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book.Financial Risk Modelling and Portfolio Optimisation with R:Demonstrates techniques in modelling financial risks and applying portfolio optimisation techniques as well as recent advances in the field. Introduces stylised facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalised hyperbolic distribution, volatility modelling and concepts for capturing dependencies.Explores portfolio risk concepts and optimisation with risk constraints.Enables the reader to replicate the results in the book using R code.Is accompanied by a supporting website featuring examples and case studies in R.Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimisation will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study. 
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Book details

List price: $66.95
Copyright year: 2013
Publisher: John Wiley & Sons, Limited
Publication date: 12/7/2012
Binding: Hardcover
Pages: 374
Size: 6.00" wide x 9.00" long x 0.80" tall
Weight: 1.694
Language: English

List of Abbreviations
A Brief Course in R
Origin and Development
Getting Help
Working with R
Classes, Methods and Functions
The Accompanying Package FRAPO
Financial Market Data
Stylised Facts of Financial Market Returns
Stylised Facts for Univariate Series
Stylised Facts for Multivariate Series
Implications for Risk Models
Measuring Risks
Synopsis of Risk Measures
Portfolio Risk Concepts
Modern Portfolio Theory
Markowitz Portfolios
Empirical Mean-Variance Portfolios
Risk Modelling ����
Suitable Distributions for Returns
The Generalised Hyperbolic Distribution
The Generalised Lambda Distribution
Synopsis of R Packages for GHYP
The package fBasics
The package GeneralizedHyperbolic
The package ghyp
The package QRM
The package SkewHyperbolic
The package VarianceGamma
Synopsis of R Packages for GLD
The package Davies
The package fBasics
The package GLDEX
The package gld
The package lmomco
Applications of the GHD to Risk Modelling
Fitting stock returns to the GHD
Risk assessment with the GHD
Stylised Facts Revisited
Applications of the GLD to Risk Modelling and Data Analysis
VaR for a Single Stock
Shape Triangle for FTSE 100 Constituents
Extreme Value Theory
Extreme Value Methods and Models
The Block Maxima Approach
The r-largest Order Models
The Peaks-over-Threshold Approach
Synopsis of R Packages
The package evd
The package evdbayes
The package evir
The package fExtremes
The packages ismev and extRemes
The package POT
The package QRM
The package Renext
Empirical Applications of EVT
Section Outline
Block Maxima Model for Siemens
r-Block Maxima for BMW
POT-Method for Boeing
Modelling Volatility
The class of ARCH-models
Synopsis of R Packages
The package bayesGARCH
The package ccgarch
The package fGarch
The package gogarch
The packages rugarch and rmgarch
The package tseries
Empirical Application of Volatility Models
Modelling Dependence
Correlation, Dependence and Distributions
Correlations and Dependence Revisited
Classification and Kinds of Copulae
Synopsis of R Packages
The package BLCOP
The packages copula and nacopula
The package fCopulae
The package gumbel
The package QRM
Empirical Applications of Copulae
GARCH- Copula Model
Mixed Copulae Approaches
Portfolio Optimisation Approaches
Robust Portfolio Optimisation
Robust Statistics
Selected Robust Estimators
Robust Optimisation
Uncertainty Sets and Problem Formulation
Synopsis of R Packages
The package covRobust
The package fPortfolio
The package MASS
The package robustbase
The package robust
The package rrcov
The package Rsocp
Empirical Application
Portfolio Simulation: Robust vs. Classical Statistics
Portfolio Back Test: Robust vs. Classical Statistics
Portfolio Back Test: Robust Optimisation
Diversification Reconsidered
Most-Diversified Portfolio
Risk Contribution Constrained Portfolios
Optimal Tail-Dependent Portfolios
Synopsis of R Packages
The packages DEoptim and RcppDE
The package FRAPO
The package PortfolioAnalytics
Empirical Applications
Comparison of Approaches
Optimal Tail-Dependent Portfolio against Benchmark
Limiting Contributions to Expected Shortfall
Risk-Optimal Portfolios
Mean-VaR Portfolios
Optimal CVaR Portfolios
Optimal Draw Down Portfolios
Synopsis of R Packages
The package fPortfolio
The package FRAPO
R packages for Linear Programming
The package PerformanceAnalytics
Empirical Applications
Minimum-CVaR versus Minimum-Variance Portfolios
Draw Down Constrained Portfolios
Backtest Comparison for Stock Portfolio
Tactical Asset Allocation
Survey of Selected Time Series Models
Univariate Time Series Models
Multivariate Time Series Models
Black-Litterman Approach
Copula Opinion and Entropy Pooling
The COP-model
The EP-model
Synopsis of R packages
The package BLCOP
The package dse
The package fArma
The package forecast
The package MSBVAR
The package PairTrading
The packages urca and vars
Empirical Applications
Black-Litterman Portfolio Optimisation
Copula Opinion Pooling
Protection Strategies
Package Overview
Packages in Alphabetical Order
Packages Ordered by Topic
Time Series Data
Date-Time Classes
Irregular-Spaced TimeSeries
The package timeSeries
The package zoo
The packages tframe and xts
Back testing and Reporting of Portfolio Strategies
R Packages for Back testing
R Facilities for Reporting
Interfacing Databases
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