Verfügbarkeit: Financial risk modelling and portfolio optimization with R

Financial risk modelling and portfolio optimization with R:

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Bibliographische Detailangaben
1. Verfasser:	Pfaff, Bernhard (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Chichester, West Sussex, United Kingdom Wiley 2016
Ausgabe:	Second edition
Schlagworte:	BUSINESS & ECONOMICS / Finance Mathematisches Modell Wirtschaft Financial risk / Mathematical models Portfolio management R (Computer program language) R > Programm Portfolio Selection Risikomanagement Portfoliomanagement
Online-Zugang:	FAB01 FRO01 FUBA1 HWR01 TUM01 UBG01 UBR01 UBT01 UEI03 UPA01 Volltext Inhaltsverzeichnis
Beschreibung:	MOTIVATION. Introduction -- A brief course in R -- Financial market data -- Measuring risks -- Modern portfolio theory -- RISK MODELLING. Suitable distributions for returns -- Extreme value theory -- Modelling volatility -- Modelling dependence -- PORTFOLIO OPTIMIZATION APPROACHES. Robust portfolio optimization -- Diversification reconsidered -- Risk-optimal portfolios -- Tactical asset allocation -- Probabilistic utility -- Package overview -- Time series data -- Back-testing and reporting of portfolio strategies -- Technicalities. - Includes bibliographical references and index
Beschreibung:	1 Online-Ressource (xx, 426 Seiten)
ISBN:	9781119119685 9781119119692
DOI:	10.1002/9781119119692

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Datensatz im Suchindex

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adam_text	Titel: Financial risk modelling and portfolio optimization with R Autor: Pfaff, Bernhard Jahr: 2016 Contents Preface to the Second Edition xi Preface xiii Abbreviations xv About the Companion Website xix PART I MOTIVATION 1 1 Introduction 3 Reference 5 2 A brief course in R 6 2.1 Origin and development 6 2.2 Getting help 7 2.3 Working with R 10 2.4 Classes, methods, and functions 12 2.5 The accompanying package FRAPO 22 References 28 3 Financial market data 29 3.1 Stylized facts of financial market returns 29 3.1.1 Stylized facts for univariate series 29 3.1.2 Stylized facts for multivariate series 32 3.2 Implications for risk models 35 References 36 4 Measuring risks 37 4.1 Introduction 37 4.2 Synopsis of risk measures 37 4.3 Portfolio risk concepts 42 References 44 5 Modern portfolio theory 46 5.1 Introduction 46 vi CONTENTS 5.2 Markowitz portfolios 47 5.3 Empirical mean-variance portfolios 50 References PART II RISK MODELLING 55 6 Suitable distributions for returns 57 6 .1 Preliminaries 57 6.2 The generalized hyperbolic distribution 57 6.3 The generalized lambda distribution 60 6.4 Synopsis of R packages for GHD 66 6.4.1 The package fBasics 66 6.4.2 The package GeneralizedHyperbolic 67 6.4.3 The package ghyp 69 6.4.4 The package QRM 70 6.4.5 The package SkewHyperbolic 70 6.4.6 The package VarianceGamma 71 6.5 Synopsis of R packages for GLD 71 6.5.1 The package Davies 71 6.5.2 The package fBasics 72 6.5.3 The package gld 73 6.5.4 The package lmomco 73 6.6 Applications of the GHD to risk modelling 74 6.6.1 Fitting stock returns to the GHD 74 6.6.2 Risk assessment with the GHD 77 6.6.3 Stylized facts revisited 80 6.7 Applications of the GLD to risk modelling and data analysis 82 6.7.1 VaR for a single stock ? 82 6.7.2 Shape triangle for FTSE 100 constituents 84 References 86 7 Extreme value theory 89 7.1 Preliminaries 89 7.2 Extreme value methods and models 90 7.2.1 The block maxima approach 90 7.2.2 The rth largest order models 91 7.2.3 The peaks-over-threshold approach 92 7.3 Synopsis of R packages 94 7.3.1 The package evd 94 7.3.2 The package evdbayes 95 7.3.3 The package evir 96 7.3.4 The packages extRemes and in2extRemes 98 CONTENTS vii 7.3.5 The package fExtremes 99 7.3.6 The package ismev 101 7.3.7 The package QRM 101 7.3.8 The packages Renext and RenextGUI 102 7.4 Empirical applications of EVT 103 7.4.1 Section outline 103 7.4.2 Block maxima model for Siemens 103 7.4.3 r-block maxima for BMW 107 7.4.4 POT method for Boeing 110 References 115 8 Modelling volatility 116 8.1 Preliminaries 116 8.2 The class of ARCH models 116 8.3 Synopsis of R packages 120 8.3.1 The package bayesGARCH 120 8.3.2 The package ccgarch 121 8.3.3 The package fGarch 122 8.3.4 The package GEVStableGarch 122 8.3.5 The package gogarch 123 8.3.6 The package lgarch 123 8.3.7 The packages rugarch and rmgarch 125 8.3.8 The package tseries 127 8.4 Empirical application of volatility models 128 References 130 9 Modelling dependence 133 9.1 Overview 133 9.2 Correlation, dependence, and distributions 133 9.3 Copulae 136 9.3.1 Motivation 136 9.3.2 Correlations and dependence revisited 137 9.3.3 Classification of copulae 139 9.4 Synopsis of R packages 142 9.4.1 The package BLCOP 142 9.4.2 The package copula 144 9.4.3 The package fCopulae 146 9.4.4 The package gumbel 147 9.4.5 The package QRM 148 9.5 Empirical applications of copulae 148 9.5.1 GARCH-copula model 148 9.5.2 Mixed copula approaches 155 References 157 CONTENTS viii PART III PORTFOLIO OPTIMIZATION APPROACHES 161 10 Robust portfolio optimization 163 10.1 Overview 63 10.2 Robust statistics 64 10.2.1 Motivation * 64 10.2.2 Selected robust estimators 165 10.3 Robust optimization *68 10.3.1 Motivation 168 10.3.2 Uncertainty sets and problem formulation 168 10.4 Synopsis of R packages 174 10.4.1 The package covRobust 1 74 10.4.2 The package fPortfolio 174 10.4.3 The package MASS 175 10.4.4 The package robustbase 176 10.4.5 The package robust 176 10.4.6 The package rrcov 178 10.4.7 Packages for solving SOCPs 179 10.5 Empirical applications 180 10.5.1 Portfolio simulation: robust versus classical statistics 180 10.5.2 Portfolio back test: robust versus classical statistics 186 10.5.3 Portfolio back-test: robust optimization 190 References 195 11 Diversification reconsidered 198 11.1 Introduction 198 11.2 Most-diversified portfolio 199 11.3 Risk contribution constrained portfolios 201 11.4 Optimal tail-dependent portfolios 204 11.5 Synopsis of R packages 207 11.5.1 The package cccp 207 11.5.2 The packages DEoptim, DEoptimR, and RcppDE 207 11.5.3 The package FRAPO 210 11.5.4 The package PortfolioAnalytics 211 11.6 Empirical applications 212 11.6.1 Comparison of approaches 212 11.6.2 Optimal tail-dependent portfolio against benchmark 216 11.6.3 Limiting contributions to expected shortfall 221 References 226 12 Risk-optimal portfolios 228 12.1 Overview 228 12.2 Mean-VaR portfolios 229 12.3 Optimal C VaR portfolios 234 12.4 Optimal draw-down portfolios 238 CONTENTS IX 12.5 Synopsis of R packages 241 1 2.5. 1 The package fPortfolio 241 12.5.2 The package FRAPO 243 12.5.3 Packages for linear programming 245 12.5.4 The package PerformanceAnalytics 249 12.6 Empirical applications 251 12.6.1 Minimum-CVaR versus minimum-variance portfolios 251 12.6.2 Draw-down constrained portfolios 254 12.6.3 Back-test comparison for stock portfolio 260 12.6.4 Risk surface plots 265 References 272 13 Tactical asset allocation 274 13.1 Overview 274 13.2 Survey of selected time series models 275 13.2.1 Univariate time series models 275 13.2.2 Multivariate time series models 281 13.3 The Black-Litterman approach 289 13.4 Copula opinion and entropy pooling 292 13.4.1 Introduction 292 13.4.2 The COP model 292 13.4.3 The EP model 293 13.5 Synopsis of R packages 295 13.5.1 The package BLCOP 295 13.5.2 The package dse 297 13.5.3 The package fArma 300 13.5.4 The package forecast 301 13.5.5 The package MSB VAR 302 1 3.5.6 The package PortfolioAnalytics 304 13.5.7 The packages urea and vars 304 13.6 Empirical applications 307 13.6.1 Black-Litterman portfolio optimization 307 13.6.2 Copula opinion pooling 313 13.6.3 Entropy pooling 318 13.6.4 Protection strategies 324 References 334 14 Probabilistic utility 339 14.1 Overview 339 14.2 The concept of probabilistic utility 340 14.3 Markov chain Monte Carlo 342 14.3.1 Introduction 342 14.3.2 Monte Carlo approaches 343 14.3.3 Markov chains 347 14.3.4 Metropolis-Hastings algorithm 349 x CONTENTS 14.4 Synopsis of R packages 354 14.4.1 Packages for conducting MCMC 354 14.4.2 Packages for analyzing MCMC 358 14.5 Empirical application 362 14.5.1 Exemplary utility function 362 14.5.2 Probabilistic versus maximized expected utility 366 14.5.3 Simulation of asset allocations 369 References 375 Appendix A Package overview 378 A.l Packages in alphabetical order 378 A. 2 Packages ordered by topic 382 References 386 Appendix B Time series data 391 B. l Date/time classes 391 B.2 The ts class in the base package stats 395 B.3 Irregularly spaced time series 395 B.4 The package timeSeries 397 B.5 The package zoo 399 B. 6 The packages tframe and xts 401 References 404 Appendix C Back-testing and reporting of portfolio strategies 406 C. 1 R packages for back-testing 406 C.2 R facilities for reporting 407 C.3 Interfacing with databases 407 References 408 Appendix D Technicalities 411 Reference 4 j j Index 413
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id	DE-604.BV043827085
illustrated	Not Illustrated
indexdate	2024-07-10T07:36:08Z
institution	BVB
isbn	9781119119685 9781119119692
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-029237955
oclc_num	956700960 968277252
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owner	DE-91 DE-BY-TUM DE-861 DE-355 DE-BY-UBR DE-703 DE-739 DE-188 DE-2070s DE-1043 DE-945
owner_facet	DE-91 DE-BY-TUM DE-861 DE-355 DE-BY-UBR DE-703 DE-739 DE-188 DE-2070s DE-1043 DE-945
physical	1 Online-Ressource (xx, 426 Seiten)
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publishDate	2016
publishDateSearch	2016
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publisher	Wiley
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spelling	Pfaff, Bernhard Verfasser (DE-588)13235795X aut Financial risk modelling and portfolio optimization with R Bernhard Pfaff Second edition Chichester, West Sussex, United Kingdom Wiley 2016 1 Online-Ressource (xx, 426 Seiten) txt rdacontent c rdamedia cr rdacarrier MOTIVATION. Introduction -- A brief course in R -- Financial market data -- Measuring risks -- Modern portfolio theory -- RISK MODELLING. Suitable distributions for returns -- Extreme value theory -- Modelling volatility -- Modelling dependence -- PORTFOLIO OPTIMIZATION APPROACHES. Robust portfolio optimization -- Diversification reconsidered -- Risk-optimal portfolios -- Tactical asset allocation -- Probabilistic utility -- Package overview -- Time series data -- Back-testing and reporting of portfolio strategies -- Technicalities. - Includes bibliographical references and index BUSINESS & ECONOMICS / Finance bisacsh Mathematisches Modell Wirtschaft Financial risk / Mathematical models Portfolio management R (Computer program language) R Programm (DE-588)4705956-4 gnd rswk-swf Portfolio Selection (DE-588)4046834-3 gnd rswk-swf Risikomanagement (DE-588)4121590-4 gnd rswk-swf Portfoliomanagement (DE-588)4115601-8 gnd rswk-swf Portfolio Selection (DE-588)4046834-3 s Portfoliomanagement (DE-588)4115601-8 s R Programm (DE-588)4705956-4 s Risikomanagement (DE-588)4121590-4 s 1\p DE-604 DE-604 Erscheint auch als Druck-Ausgabe 978-1-119-11966-1 https://doi.org/10.1002/9781119119692 Verlag URL des Erstveröffentlichers Volltext HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029237955&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk
spellingShingle	Pfaff, Bernhard Financial risk modelling and portfolio optimization with R BUSINESS & ECONOMICS / Finance bisacsh Mathematisches Modell Wirtschaft Financial risk / Mathematical models Portfolio management R (Computer program language) R Programm (DE-588)4705956-4 gnd Portfolio Selection (DE-588)4046834-3 gnd Risikomanagement (DE-588)4121590-4 gnd Portfoliomanagement (DE-588)4115601-8 gnd
subject_GND	(DE-588)4705956-4 (DE-588)4046834-3 (DE-588)4121590-4 (DE-588)4115601-8
title	Financial risk modelling and portfolio optimization with R
title_auth	Financial risk modelling and portfolio optimization with R
title_exact_search	Financial risk modelling and portfolio optimization with R
title_full	Financial risk modelling and portfolio optimization with R Bernhard Pfaff
title_fullStr	Financial risk modelling and portfolio optimization with R Bernhard Pfaff
title_full_unstemmed	Financial risk modelling and portfolio optimization with R Bernhard Pfaff
title_short	Financial risk modelling and portfolio optimization with R
title_sort	financial risk modelling and portfolio optimization with r
topic	BUSINESS & ECONOMICS / Finance bisacsh Mathematisches Modell Wirtschaft Financial risk / Mathematical models Portfolio management R (Computer program language) R Programm (DE-588)4705956-4 gnd Portfolio Selection (DE-588)4046834-3 gnd Risikomanagement (DE-588)4121590-4 gnd Portfoliomanagement (DE-588)4115601-8 gnd
topic_facet	BUSINESS & ECONOMICS / Finance Mathematisches Modell Wirtschaft Financial risk / Mathematical models Portfolio management R (Computer program language) R Programm Portfolio Selection Risikomanagement Portfoliomanagement
url	https://doi.org/10.1002/9781119119692 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029237955&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT pfaffbernhard financialriskmodellingandportfoliooptimizationwithr

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