04801nam 2200637 450 991013502070332120231222063221.01-119-11967-71-119-11968-51-119-11969-3(CKB)4330000000008674(EBL)4648719(Au-PeEL)EBL4648719(CaPaEBR)ebr11249683(CaONFJC)MIL950680(OCoLC)956700960(PPN)240178912(MiAaPQ)EBC4648719(EXLCZ)99433000000000867420160906h20162016 uy 0engur|n|---|||||rdacontentrdamediardacarrierFinancial risk modelling and portfolio optimization with R /Bernhard PfaffSecond edition.Chichester, [England] :Wiley,2016.©20161 online resource (497 p.)THEi Wiley ebooksDescription based upon print version of record.1-119-11966-9 Includes bibliographical references at the end of each chapters and index.Title Page; Copyright; Table of Contents; Preface to the Second Edition; Preface; Abbreviations; About the Companion Website; Part I: Motivation; Chapter 1: Introduction; Reference; Chapter 2: A brief course in R; 2.1 Origin and development; 2.2 Getting help; 2.3 Working with R; 2.4 Classes, methods, and functions; 2.5 The accompanying package FRAPO; References; Chapter 3: Financial market data; 3.1 Stylized facts of financial market returns; 3.2 Implications for risk models; References; Chapter 4: Measuring risks; 4.1 Introduction; 4.2 Synopsis of risk measures; 4.3 Portfolio risk conceptsReferencesChapter 5: Modern portfolio theory; 5.1 Introduction; 5.2 Markowitz portfolios; 5.3 Empirical mean-variance portfolios; References; Part II: Risk modelling; Chapter 6: Suitable distributions for returns; 6.1 Preliminaries; 6.2 The generalized hyperbolic distribution; 6.3 The generalized lambda distribution; 6.4 Synopsis of R packages for GHD; 6.5 Synopsis of R packages for GLD; 6.6 Applications of the GHD to risk modelling; 6.7 Applications of the GLD to risk modelling and data analysis; References; Chapter 7: Extreme value theory; 7.1 Preliminaries7.2 Extreme value methods and models7.3 Synopsis of R packages; 7.4 Empirical applications of EVT; References; Chapter 8: Modelling volatility; 8.1 Preliminaries; 8.2 The class of ARCH models; 8.3 Synopsis of R packages; 8.4 Empirical application of volatility models; References; Chapter 9: Modelling dependence; 9.1 Overview; 9.2 Correlation, dependence, and distributions; 9.3 Copulae; 9.4 Synopsis of R packages; 9.5 Empirical applications of copulae; References; Part III: Portfolio optimization approaches; Chapter 10: Robust portfolio optimization; 10.1 Overview; 10.2 Robust statistics10.3 Robust optimization10.4 Synopsis of R packages; 10.5 Empirical applications; References; Chapter 11: Diversification reconsidered; 11.1 Introduction; 11.2 Most-diversified portfolio; 11.3 Risk contribution constrained portfolios; 11.4 Optimal tail-dependent portfolios; 11.5 Synopsis of R packages; 11.6 Empirical applications; References; Chapter 12: Risk-optimal portfolios; 12.1 Overview; 12.2 Mean-VaR portfolios; 12.3 Optimal CVaR portfolios; 12.4 Optimal draw-down portfolios; 12.5 Synopsis of R packages; 12.6 Empirical applications; References; Chapter 13: Tactical asset allocation13.1 Overview13.2 Survey of selected time series models; 13.3 The Black-Litterman approach; 13.4 Copula opinion and entropy pooling; 13.5 Synopsis of R packages; References; Chapter 14: Probabilistic utility; 14.1 Overview; 14.2 The concept of probabilistic utility; 14.3 Markov chain Monte Carlo; 14.4 Synopsis of R packages; 14.5 Empirical application; References; Appendix A: Package overview; A.1 Packages in alphabetical order; A.2 Packages ordered by topic; References; Appendix B: Time series data; B.1 Date/time classes; B.2 The ts class in the base package statsB.3 Irregularly spaced time seriesTHEi Wiley ebooks.Financial riskMathematical modelsPortfolio managementR (Computer program language)Financial riskMathematical models.Portfolio management.R (Computer program language)332.0285/5133Pfaff Bernhard501178MiAaPQMiAaPQMiAaPQBOOK9910135020703321Financial risk modelling and portfolio optimization with R2179728UNINA